marronnier.ch

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Prof. Stephan ROBERT-NICOUD, PhD

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

Nuage de mots-clefs

february learning mit january neural networks deep university november models

Cohérence des mots-clefs

Mot-clef Contenu Titre Mots-clefs Description Niveaux de titre
university 110
learning 104
networks 34
november 31
neural 31

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