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Prof. Stephan ROBERT-NICOUD, PhD

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type website
title Prof. Stephan ROBERT-NICOUD, PhD
url https://www.stephan-robert.ch/
site_name Prof. Stephan ROBERT-NICOUD, PhD
image https://s0.wp.com/i/blank.jpg
image:width 200
image:height 200
locale fr_FR

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  • [H1] Prof. Stephan ROBERT-NICOUD, PhD
  • [H1] Gestion des situations de crises sanitaires (GESICA)
  • [H1] SCHOOL OF ENGINEERING AND MANAGEMENT SCHEDULING
  • [H1] ADAPTIVE TUNING OF NEURAL NETWORKS PARAMETERS FOR TIME SERIES PREDICTION
  • [H1] SYSTÈME D’INTELLIGENCE ARTIFICIELLE – RÉGULATION MÉDICALE DES URGENCES (SIA-REMU)
  • [H1] Active Learning and Autoencoders in Banking Fraud Detection (ALEA)
  • [H1] Optimizing Operating Rooms and Care Services using Deep Reinforcement Learning (OPERATE)
  • [H1] Lunch Seminars
  • [H2] Statistical Learning Research Group (Sailing)
  • [H2] 2026
  • [H2] 2025
  • [H2] 2024
  • [H2] 2023
  • [H2] 2022
  • [H2] 2021
  • [H2] 2020
  • [H2] 2019
  • [H2] 2018
  • [H2] 2023
  • [H2] 2022
  • [H2] 2021
  • [H2] 2020
  • [H2] 2019
  • [H2] 2018

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Prof. Stephan ROBERT-NICOUD, PhD extern natürliche Links
Recherche intern natürliche Links
Team extern natürliche Links
Research extern natürliche Links
Research Projects extern natürliche Links
Gestion des situations de crises sanitaires extern natürliche Links
Système d’Intelligence Artificielle – Régulation Médicale des Urgences (SIA-REMU) extern natürliche Links
Adaptive Tuning of Neural Networks Parameters for Time Series Prediction extern natürliche Links
Active Learning and Autoencoders in Banking Fraud Detection (ALEA) extern natürliche Links
Blockchain and Cryptocurrencies extern natürliche Links
Optimizing Operating Rooms and Care Services using Deep Reinforcement Learning (OPERATE) extern natürliche Links
WhiteBoard Seminars extern natürliche Links
Jobs extern natürliche Links
Engineering extern natürliche Links
Student Projects extern natürliche Links
Study abroad Students Testamonials extern natürliche Links
Publications extern natürliche Links
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Teaching extern natürliche Links
Doctoral Classes extern natürliche Links
Analysis of Sequential Data extern natürliche Links
Apprentissage supervisé (APV) extern natürliche Links
Introduction à la science des données (ISD) extern natürliche Links
Apprentissage par Réseaux de Neurones artificiels (ARN) extern natürliche Links
Previous courses extern natürliche Links
Summer University extern natürliche Links
2020 and 2021 Summer University extern natürliche Links
2019 Summer University extern natürliche Links
2018 Summer University extern natürliche Links
SU’18-CSCS, Pictures extern natürliche Links
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2016 Summer University extern natürliche Links
2015 Summer University extern natürliche Links
2014 Summer University extern natürliche Links
2013 Summer University extern natürliche Links
News (press) extern natürliche Links
Private extern natürliche Links
Bistro du Marronnier extern natürliche Links
Chestnut Tree Videos extern natürliche Links
Permaculture extern natürliche Links
Family extern natürliche Links
Reading Group in Contemporary Evangelical Philosophy extern natürliche Links
Videos-teaching extern natürliche Links
Mérites ponliers extern natürliche Links
Contact extern natürliche Links
Gestion des situations de crises sanitaires (GESICA) extern natürliche Links
SCHOOL OF ENGINEERING AND MANAGEMENT SCHEDULING extern natürliche Links
Active Learning and Autoencoders in Banking Fraud Detection (ALEA) extern natürliche Links
Optimizing Operating Rooms and Care Services using Deep Reinforcement Learning (OPERATE) extern natürliche Links
Advanced topics in theorem proving extern natürliche Links
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs extern natürliche Links
miniCTX: Neural Theorem Proving with (Long-)Contexts extern natürliche Links
Lean-STaR: Learning to Interleave Thinking and Proving extern natürliche Links
ImProver: Agent-Based Automated Proof Optimization extern natürliche Links
AI’s Models of the World, and Ours | Theoretically Speaking extern natürliche Links
Do Mathematicians Need Computers? extern natürliche Links
LMs for Autoformalization+Theorem Proving extern natürliche Links
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models extern natürliche Links
Autoformalization with Large Language Models extern natürliche Links
Autoformalizing Euclidean Geometry extern natürliche Links
New Simple Optimizer: Muon extern natürliche Links
AlphaProof, When RL meets formal maths extern natürliche Links
AI achieves silver-medal standard solving International Mathematical Olympiad problems extern natürliche Links
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm extern natürliche Links
The Future of Mathematics? extern natürliche Links
Building the Mathematical Library of the Future extern natürliche Links
Mystères mathématiques d’intelligences pas si artificielles extern natürliche Links
Le pouvoir de la symétrie extern natürliche Links
Realizing Nakamoto’s Dream: One-Time Signatures, Garbled Circuits & Zero-Knowledge Proofs extern natürliche Links
Where is Mathematics Going? extern natürliche Links
Multimodal Agent extern natürliche Links
OSWORLD: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments extern natürliche Links
AGUVIS: Unified Pure Vision Agents For Autonomous GUI Interaction extern natürliche Links
Multimodal Autonomous Agents extern natürliche Links
Mind2Web: Towards a Generalist Agent for the Web extern natürliche Links
WebArena: A Realistic Web Environment for Building Autonomous Agents extern natürliche Links
VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks extern natürliche Links
Tree Search for Language Model Agent extern natürliche Links
Coding Agents and AI for Vulnerability Detection extern natürliche Links
Interactive Tools Substantially Assist LM Agents in Finding Security Vulnerabilities extern natürliche Links
From Naptime to Big Sleep: Using Large Language Models To Catch Vulnerabilities In Real-World Code extern natürliche Links
Open Training Recipes for Reasoning in Language Models, extern natürliche Links
Tulu 3: Pushing Frontiers in Open Language Model Post-Training extern natürliche Links
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback extern natürliche Links
OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs extern natürliche Links
Grokked Transformers are Implicit Reasoners: A Mechanistic Journey to the Edge of Generalization extern natürliche Links
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models extern natürliche Links
Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents extern natürliche Links
Learning to Self-Improve & Reason with LLMs extern natürliche Links
Direct Preference Optimization: Your Language Model is Secretly a Reward Model extern natürliche Links
Iterative Reasoning Preference Optimization extern natürliche Links
Chain-of-Verification Reduces Hallucination in Large Language Models extern natürliche Links
Spectral Zeta Function of Graphs and the Riemann Zeta Function extern natürliche Links
Inference-Time Techniques for LLM Reasoning extern natürliche Links
L’interview d’Hugo Duminil-Copin, médaillé Fields extern natürliche Links
David Pouapre extern natürliche Links
Launch of the Gesica project extern natürliche Links
BioTech Campus extern natürliche Links
Prof. Hugo Duminil Copain (Fields Medalist 2022) extern natürliche Links
Post extern natürliche Links
Robert Mardini, extern natürliche Links
HUG extern natürliche Links
ICRC (International Comettee of the Red Cross) extern natürliche Links
LLM Scientist Toolkit, Key Insights from NeurIPS extern natürliche Links
Official interview extern natürliche Links
Sequence to Sequence Learning with Neural Networks extern natürliche Links
, Evaluating Large Language Models – Principles, Approaches, and Applications extern natürliche Links
Graph Learning: Principles, Challenges, and Open Directions extern natürliche Links
Physics of Language Models extern natürliche Links
CLIMB talk with Martin Wainwright extern natürliche Links
Mastering LLM Inference Optimization From Theory to Cost Effective Deployment extern natürliche Links
Diffusion Models extern natürliche Links
GAN, Video, point Cloud extern natürliche Links
Vision Transformer extern natürliche Links
Long-Context LLMs extern natürliche Links
Transformer and LLM extern natürliche Links
Mathematical Discoveries from program Search with Large Language Models extern natürliche Links
How should we evaluate long-context language models extern natürliche Links
« What robots have taught me about machine learning » extern natürliche Links
Abide by the law and follow the flow: conservation laws for gradient flows extern natürliche Links
paper extern natürliche Links
Causal Imputation and Causal Disentanglement extern natürliche Links
Optimal Quantile Estimation for Streams extern natürliche Links
Data Contribution Estimation for Machine Learning extern natürliche Links
Do You Prefer Learning with Preferences? extern natürliche Links
Transformers for Bootstrapperd Amplitudes, extern natürliche Links
Chaining: a long story (Abel lecture) extern natürliche Links
Nobel Prize lectures in physics extern natürliche Links
Sparsification of Gaussian Processes extern natürliche Links
Inverse Reinforcement Learning extern natürliche Links
Learning-Based Solutions for Inverse Problems extern natürliche Links
The Era of 1-bit LLMs-All Large Language Models are in 1.58 Bits extern natürliche Links
paper extern natürliche Links
The Many Faces of Responsible AI extern natürliche Links
Pretrained diffusion is all we need: a journey beyond training distribution extern natürliche Links
Heavy Tails in ML: Structure, Stability, Dynamics extern natürliche Links
Unsupervised Pre-Training:Contrastive Learning extern natürliche Links
class link extern natürliche Links
Direct Preference Optimization: Your Language Model is Secretly a Reward Model extern natürliche Links
paper extern natürliche Links
Scaling Data-Constrained Language Models (at NeurIPS) extern natürliche Links
long version extern natürliche Links
paper extern natürliche Links
Are Emergent Abilities of Large Language Models a Mirage? extern natürliche Links
paper extern natürliche Links
Statistical Applications of Wasserstein Gradient Flows extern natürliche Links
Pareto Invariant Risk Minimization: Towards Mitigating The Optimization Dilemma in Out-of-Distribution Generalization extern natürliche Links
Artificial Intelligence, Ethics, and a Right to a Human Decision extern natürliche Links
Analyzing Transfer Learning Bounds through Distributional Robustness extern natürliche Links
Designing High-Dimensional Closed-Loop Optimal Control Using Deep Neural Networks extern natürliche Links
Climate modeling with AI: Hype or Reality? extern natürliche Links
Generative Models and Physical Processes extern natürliche Links
Quantifying causal influence in time series and beyond extern natürliche Links
Reasoning and Abstraction as Challenges for AI extern natürliche Links
Steering AI for the Public Good: A Dialogue for the Future extern natürliche Links
Topological Modeling of Complex Data extern natürliche Links
Transformers United extern natürliche Links
Variational Autoencoder extern natürliche Links
Could a Large Language Model be Conscious? extern natürliche Links
Transformers and Pretraining extern natürliche Links
Introduction to self-attention and transformers extern natürliche Links
GPT-3 & Beyond extern natürliche Links
Reinforcement Learning 10 (Classic Games Case Study) extern natürliche Links
How to increase certainty in predictive modeling extern natürliche Links
, Reinforcement Learning 8 (Advanced Topics in Deep RL) extern natürliche Links
Reinforcement Learning 7 (Planning and Models) extern natürliche Links
Reinforcement Learning 6 (Policy Gradients and Actor Critics) extern natürliche Links
Reinforcement Learning 4 (Model-Free Prediction and Control) extern natürliche Links
Offline Reinforcement Learning extern natürliche Links
Reinforcement Learning 2 (Exploration and Exploitation) extern natürliche Links
Reinforcement Learning 1 extern natürliche Links
RLbook2020 extern natürliche Links
Introduction to Algebraic Topology extern natürliche Links
Signal Recovery with Generative Priors extern natürliche Links
Learning-Based Low-Rank Approximations extern natürliche Links
paper extern natürliche Links
General graph problems with neural networks extern natürliche Links
The Transformer Network for the Traveling Salesman Problem extern natürliche Links
Artificial Intelligence in Acute Medecine, From theory to applications extern natürliche Links
Attention, Learn to Solve Routing Problems! extern natürliche Links
Why Did Quantum Entanglement Win the Nobel Prize in Physics? extern natürliche Links
Sixty Symbols – Spooky Action at a Distance (Bell’s Inequality) extern natürliche Links
EigenGame PCA as a Nash Equilibrium extern natürliche Links
Deep Semi-Supervised Anomaly Detection extern natürliche Links
Discovering faster matrix multiplication algorithms with reinforcement learning extern natürliche Links
Compressing Variational Bayes extern natürliche Links
From Machine Learning to Autonomous Intelligence extern natürliche Links
Diffusion Probabilistic Models extern natürliche Links
Attention and Memory in Deep Learning extern natürliche Links
Transformers and Self-Attention extern natürliche Links
Ensuring Safety in Online Reinforcement Learning by Leveraging Offline Data extern natürliche Links
Geometric Deep Learning: The Erlangen Programme of ML extern natürliche Links
The Devil is in the Tails and Other Stories of Interpolation extern natürliche Links
Gaussian multiplicative chaos: applications and recent developments extern natürliche Links
Statistical mechanics arising from random matrix theory extern natürliche Links
Stop Explaining Black Box Machine Learning Models extern natürliche Links
Network Calculus extern natürliche Links
Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning extern natürliche Links
Generation and Simulation of Synthetic Datasets with Copulas extern natürliche Links
arXiv:2203.17250 extern natürliche Links
Combining Reinforcement Learning & Constraint Programming for Combinator… extern natürliche Links
Deep Reinforcement Learning at the Edge of the Statistical Precipice extern natürliche Links
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies extern natürliche Links
I Can’t Believe Latent Variable Models Are Not Better extern natürliche Links
From System 1 Deep Learning to System 2 Deep Learning extern natürliche Links
Latent Dirichlet Allocation extern natürliche Links
Online Learning for Latent Dirichlet Allocation extern natürliche Links
On the Expressivity of Markov Reward extern natürliche Links
paper extern natürliche Links
Continuous Time Dynamic Programming — The Hamilton-Jacobi-Bellman Equation extern natürliche Links
Computational Barriers in Statistical Estimation and Learning extern natürliche Links
Offline Deep Reinforcement Learning Algorithms extern natürliche Links
Infusing Physics and Structure into Machine extern natürliche Links
Robust Predictable Control extern natürliche Links
web page extern natürliche Links
paper extern natürliche Links
Recent Advances in Integrating Machine Learning and Combinatorial Optimization – Tutorial at AAAI-21 extern natürliche Links
Attention and Transformer Networks extern natürliche Links
Yes, Generative Models Are The New Sparsity extern natürliche Links
The Knockoffs Framework: New Statistical Tools for Replicable Selections extern natürliche Links
Compositional Dynamics Modeling for Physical Inference and Control extern natürliche Links
Safe and Efficient Exploration in Reinforcement Learning extern natürliche Links
Luis von Ahn extern natürliche Links
Contrastive Learning: A General Self-supervised Learning Approach extern natürliche Links
https://arxiv.org/abs/2004.11362 extern natürliche Links
Adversarial Robustness – Theory and Practice extern natürliche Links
Recent Developments in Over-parametrized Neural Networks extern natürliche Links
Feedback Control Perspectives on Learning extern natürliche Links
Self-Supervised Learning & World Models extern natürliche Links
Theoretical Foundations of Graph Neural Networks extern natürliche Links
Deep Implicit Layers extern natürliche Links
Bayesian Deep Learning and Probabilistic Model Construction extern natürliche Links
Learning Ising Models from One, Ten or a Thousand Samples extern natürliche Links
Deconstructing the Blockchain to Approach Physical Limits extern natürliche Links
Federated Learning and Analytics at Google and Beyond extern natürliche Links
Equivariant Networks and Natural Graph Networks extern natürliche Links
1 extern natürliche Links
2 extern natürliche Links
3 extern natürliche Links
4 extern natürliche Links
Machine Learning with Signal Processing extern natürliche Links
A Function Approximation of Perspective on Sensory Representations extern natürliche Links
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent extern natürliche Links
Neural Tangent Kernel: Convergence and Generalization in Neural Networks extern natürliche Links
On Exact Computation with an Infinitely Wide Neural Net extern natürliche Links
Spectrum Dependent Learning Curves in Kernel Regression and Wide extern natürliche Links
Hopfield Networks in 2021 extern natürliche Links
Influence: Using Disentangled Representations to Audit Model Predictions extern natürliche Links
Offline Reinforcement Learning extern natürliche Links
Stanford Seminar (part 2) – Information Theory of Deep Learning extern natürliche Links
New Theory Cracks Open the Black Box of Deep Learning extern natürliche Links
Computer vision: who is harmed and who benefits? extern natürliche Links
Smart Interfaces for Human-Centered AI extern natürliche Links
Anthropological/Artificial Intelligence & the HAI extern natürliche Links
Faception extern natürliche Links
HireVue extern natürliche Links
Our Data Bodies extern natürliche Links
Network Telemetry and Analytics for tomorrows Zero Touch Operation Network extern natürliche Links
Representation Learning Without Labels extern natürliche Links
Active Learning: From Theory to Practice extern natürliche Links
Stanford Seminar – Machine Learning for Creativity, Interaction, and Inclusion, extern natürliche Links
pdf extern natürliche Links
LambdaNetworks: Modeling long-range Interactions without Attention (Paper Explained, ICLR 2021 submission) extern natürliche Links
Artificial Stupidity: The New AI and the Future of Fintech extern natürliche Links
LSTM is dead. Long Live Transformers! extern natürliche Links
LSTM paper extern natürliche Links
LSTM Diagrams- Understanding LSTM extern natürliche Links
Attention is all you need extern natürliche Links
Illustrated Attention extern natürliche Links
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding extern natürliche Links
Deep contextualized word representations extern natürliche Links
huggingface/transformers extern natürliche Links
Machine Learning Projects Against COVID-19 extern natürliche Links
Kernel and Deep Regimes in Overparameterized Learning extern natürliche Links
Energy-based Approaches to Representation Learning, extern natürliche Links
Learnability can be undecidable extern natürliche Links
On Learnability with Computable Learners extern natürliche Links
Generalized Resilience and Robust Statistics extern natürliche Links
Slides extern natürliche Links
Generalized Resilience and Robust Statistics extern natürliche Links
Outlier analysis extern natürliche Links
From Classical Statistics to Modern Machine Learning extern natürliche Links
To Understand Deep Learning We Need to Understand Kernel Learning extern natürliche Links
Kernel Regression Estimate extern natürliche Links
Nearest Neighbor Pattern Classification, Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate extern natürliche Links
Overparameterized Neural Networks Can Implement Associative Memory extern natürliche Links
Reconciling modern machine-learning practice and the classical bias–variance trade-off extern natürliche Links
High-dimensional dynamics of generalization error in neural networks extern natürliche Links
Automatic Machine Learning, part 3 extern natürliche Links
Slides part 3 extern natürliche Links
Slides parts 1-2, extern natürliche Links
Neural Architecture Search: A Survey. extern natürliche Links
Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures extern natürliche Links
Automatically-Tuned Neural Networks extern natürliche Links
Neural Architecture Search with Reinforcement Learning, extern natürliche Links
An Evolutionary Algorithm that Constructs Recurrent Neural Networks extern natürliche Links
Evolving Neural Networks through Augmenting Topologies extern natürliche Links
Evolving Deep Neural Networks extern natürliche Links
Regularized Evolution for Image Classifier Architecture Search extern natürliche Links
Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces extern natürliche Links
Neural Architecture Search with Bayesian Optimisation and Optimal Transport extern natürliche Links
Progressive Neural Architecture Search extern natürliche Links
Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search extern natürliche Links
Transfer Learning with Neural AutoML extern natürliche Links
Net2Net: Accelerating Learning via Knowledge Transfer extern natürliche Links
Network Morphism extern natürliche Links
Path-Level Network Transformation for Efficient Architecture Search extern natürliche Links
Efficient Architecture Search by Network Transformation extern natürliche Links
Simple and Efficient Architecture Search for CNNs extern natürliche Links
AdaNet: Adaptive Structural Learning of Artificial Neural Networks extern natürliche Links
Convolutional Neural Fabrics extern natürliche Links
Understanding and Simplifying One-Shot Architecture Search extern natürliche Links
Efficient Neural Architecture Search via Parameter Sharing extern natürliche Links
SMASH: One-Shot Model Architecture Search through HyperNetworks extern natürliche Links
DARTS: Differentiable Architecture Search extern natürliche Links
MnasNet: Platform-Aware Neural Architecture Search for Mobile extern natürliche Links
Selecting Classification Algorithms with Active Testing extern natürliche Links
Speeding up algorithm selection using average ranking and active testing by introducing runtime extern natürliche Links
Learning Hyperparameter Optimization Initializations extern natürliche Links
Hyperparameter Importance Across Datasets extern natürliche Links
Tunability: Importance of Hyperparameters of Machine Learning Algorithms extern natürliche Links
Hyperparameter Search Space Pruning – A New Component for Sequential Model-Based Hyperparameter Optimization extern natürliche Links
Gaussian Processes for Machine Learning extern natürliche Links
Scalable Gaussian process-based transfer surrogates for hyperparameter optimization extern natürliche Links
Scalable Meta-Learning for Bayesian Optimization extern natürliche Links
Book, chapter 1, extern natürliche Links
On bayesian methods for seeking the extremum extern natürliche Links
Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations extern natürliche Links
Bayesian Optimization with Exponential Convergence extern natürliche Links
Bayesian Optimization in High Dimensions via Random Embeddings extern natürliche Links
Sequential Model-Based Optimization for General Algorithm Configuration extern natürliche Links
Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces extern natürliche Links
Random Forests extern natürliche Links
Scalable Bayesian Optimization Using Deep Neural Networks extern natürliche Links
Bayesian Optimization with Robust Bayesian Neural Networks extern natürliche Links
Algorithms for Hyper-Parameter Optimization extern natürliche Links
Evolution strategies –A comprehensive introduction extern natürliche Links
The CMA Evolution Strategy: A Tutorial extern natürliche Links
CMA-ES for hyperparameters optimization of neural networks extern natürliche Links
Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves extern natürliche Links
Bilevel Programming for Hyperparameter Optimization and Meta-Learning extern natürliche Links
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters extern natürliche Links
Learning curve prediction with Bayesian neural networks extern natürliche Links
Multi-Task Bayesian Optimization extern natürliche Links
Freeze-Thaw Bayesian optimization extern natürliche Links
Multi-fidelity Bayesian Optimisation with Continuous Approximations extern natürliche Links
BOHB: Robust and Efficient Hyperparameter Optimization at Scale extern natürliche Links
Github link extern natürliche Links
Hyperband: Bandit-based configuration evaluation for hyperband parameters optimiation extern natürliche Links
Non-stochastic Best Arm Identification and Hyperparameter Optimization extern natürliche Links
Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms extern natürliche Links
Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-Learn extern natürliche Links
Efficient and Robust Automated Machine Learning, Auto-sklearn,  extern natürliche Links
GitHub link extern natürliche Links
Automating Biomedical Data Science Through Tree-Based Pipeline Optimization  extern natürliche Links
Using Knockoffs to Find Important Variables with Statistical Guarantees extern natürliche Links
Learning Noise-Invariant Representations for Robust Speech Recognition extern natürliche Links
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems extern natürliche Links
Deep Active Learning for Named Entity Recognition extern natürliche Links
Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study extern natürliche Links
Practical Obstacles to Deploying Active Learning extern natürliche Links
Active Learning with Partial Feedback extern natürliche Links
Learning From Noisy Singly-labeled Data extern natürliche Links
Deep Active Learning for Named Entity Recognition extern natürliche Links
What is the Effect of Importance Weighting in Deep Learning? extern natürliche Links
Understanding Neural Networks Through Deep Visualization extern natürliche Links
Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data extern natürliche Links
Stochastic Neural Network with Kronecker Flow extern natürliche Links
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach extern natürliche Links
Learning with Differential Privacy extern natürliche Links
Bayes point machines extern natürliche Links
The role of over-parametrization in generalization of neural networks extern natürliche Links
PAC-Bayesian Transportation Bound extern natürliche Links
Probably Approximately Correct Learning extern natürliche Links
A primer on PAC-Bayesian learning extern natürliche Links
Integrating Constraints into Deep Learning Architectures with Structured Layers extern natürliche Links
Convolutional Deep Belief Networksfor Scalable Unsupervised Learning of Hierarchical Representations extern natürliche Links
OptNet: Differentiable Optimization as a Layer in Neural Networks. extern natürliche Links
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver. extern natürliche Links
Neural Ordinary Differential Equations extern natürliche Links
Trellis Networks for Sequence Modeling. extern natürliche Links
Variational Auto Encoders extern natürliche Links
β-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework extern natürliche Links
What is consciousness, and could machines have it? extern natürliche Links
The Consciousness Prior extern natürliche Links
Better Mixing via Deep Representations extern natürliche Links
Independently Controllable Factors extern natürliche Links
On the Computational Utility of Consciousness extern natürliche Links
Self-organizing neural network that discovers surfaces in random-dot stereograms. Nature extern natürliche Links
Rebooting AI extern natürliche Links
Is Optimization the Right Language to Understand Deep Learning? extern natürliche Links
Adversarial Machine Learning extern natürliche Links
Our Mathematical Universe extern natürliche Links
Nobel Lecture: Michel Mayor, Nobel Prize in Physics 2019 extern natürliche Links
How to Successfully Harness Machine Learning to Combat Fraud and Abuse extern natürliche Links
Variational Inference: Foundations and Innovations extern natürliche Links
Variational Inference: Foundations and Innovations extern natürliche Links
Anomaly Detection using Neural Networks extern natürliche Links
Extreme Value Theory extern natürliche Links
Recurrent Neural Networks extern natürliche Links
When deep learning does not learn, extern natürliche Links
Optimality in Locally Private Estimation and Learning extern natürliche Links
Capsule Networks extern natürliche Links
A multi-perspective introduction to the EM algorithm extern natürliche Links
Theoretical Perspectives on Deep Learning extern natürliche Links
2018 ACM Turing Award extern natürliche Links
Human in the Loop Reinforcement Learning extern natürliche Links
How Graph Technology Is Changing Artificial Intelligence and Machine Learning extern natürliche Links
2017 Nobel Lectures in Physics extern natürliche Links
Accessorize to a Crime: Real and Stealthy Attacks on State-Of-The-Art Face Recognition extern natürliche Links
paper  extern natürliche Links
Build Intelligent Fraud Prevention with ML and Graphs extern natürliche Links
Active Learning: Why Smart Labeling is the Future of Data Annotation extern natürliche Links
Generalization, Interpolation, and Neural Nets extern natürliche Links
Similarity learning using deep neural networks extern natürliche Links
First lecture of MIT course 6.S091) extern natürliche Links
Dataset shift in machine learning extern natürliche Links
2015 IAAA Winner Intelligent Surgical Scheduling System extern natürliche Links
Artificial Intelligence Machine Learning Big Data, Exponential Finance extern natürliche Links
Bayesian Deep Learning with Edward (and a trick using Dropout) extern natürliche Links
Ouroboros extern natürliche Links
Cosmos Proof of Stake extern natürliche Links
Geometric Deep Learning extern natürliche Links
Deep Generative Networks as Inverse Problems extern natürliche Links
Convex Optimization and Applications extern natürliche Links
Reinforcement Learning in Healthcare: Challenges and Promise –  extern natürliche Links
Fièrement propulsé par WordPress extern natürliche Links

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models mit learning february networks university january deep november neural

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Suchbegriff Inhalt Seitentitel Suchbegriffe Seitenbeschreibung Überschriften
university 110
learning 104
networks 34
november 31
neural 31

Benutzerfreundlichkeit

URL

Domain : marronnier.ch

Länge : 13

Favoriten Icon

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Druckeigenschaften

Es konnten keine druckfreundlichen CSS-Angaben gefunden werden.

Sprache

Gut, denn Sie haben in den META-Elementen eine Sprache deklariert: fr.

Dublin Core

Diese Webseite nutzt nicht die Vorteile der Dublin Core Elemente.

Dokument

Doctype

HTML 5

Verschlüsselung

Perfekt, denn Ihre Webseite deklariert einen Zeichensatz: UTF-8.

W3C Validität

Fehler : 0

Warnungen : 0

E-Mail Datenschutz

Sehr gut, denn es wurde keine E-Mail Adresse im Klartext auf Ihrer Webseite gefunden.

Veraltetes HTML

Sehr gut! Sie verwenden aktuelle HTML Tags in Ihrem Webseitenquelltext.

Tipps zur Webseitengeschwindigkeit

Sehr gut, denn Ihre Webseite benutzt keine verschachtelten Tabellen.
Schlecht, denn es wurden CSS-Angaben in HTML-Elementen entdeckt. Diese Angaben sollten in ein entsprechendes CSS-Stylesheet verlagert werden.
Nicht so gut, denn Ihre Webseite enthält sehr viele CSS-Dateien (mehr als 4).
Perfekt, denn Ihre Webseite enthät nur wenig Javascript-Dateien.
Gut! Sie nutzen die Vorteile von gzip.

Mobile

Mobile Optimierung

Apple Icon
META Viewport Tag
Flash Inhalt

Optimierung

XML-Sitemap

Perfekt! Ihre Seite hat eine XML-Sitemap.

https://marronnier.ch/sitemap.xml
http://marronnier.ch/sitemap.xml

Robots.txt

http://marronnier.ch/robots.txt

Sehr gut! Ihre Webseite enthält eine robots.txt-Datei.

Analytics

Fehlt

Wir haben nicht ein Analyse-Tool auf dieser Website installiert zu erkennen.

Webanalyse erlaubt die Quantifizierung der Besucherinteraktionen mit Ihrer Seite. Insofern sollte zumindest ein Analysetool installiert werden. Um die Befunde abzusichern, empfiehlt sich das parallele Verwenden eines zweiten Tools.

PageSpeed Insights

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