Nicolas Le Roux
24 papers · 1999–2025 · 6 venues · across top CS/AI venues
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Research topics
Machine Learning
(20)
Optimization & Theory
(13)
Reinforcement Learning
(11)
Methods
(11)
Artificial Intelligence
(9)
Core AI
(8)
Deep Learning
(6)
Mathematics & Optimization
(6)
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Core Methods
(5)
Optimization
(5)
Architectures
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Natural Language Processing
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Generation
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Learning Paradigms
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Keywords
policy optimization
(5)
large language model
(4)
variance reduction
(3)
stochastic optimization
(3)
reinforcement learning
(3)
natural policy gradient
(2)
representation learning
(2)
linear function approximation
(2)
surrogate function
(2)
convergence rate
(2)
policy iteration
(2)
geometric analysis
(2)
policy gradient
(2)
policy evaluation
(2)
value function
(2)
function approximation
(1)
temporal difference learning
(1)
variational inference
(1)
stochastic gradient descent
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imitation learning
(1)
Papers
Fast Convergence of Softmax Policy Mirror Ascent
AISTATS 2025
fLSA: Learning Semantic Structures in Document Collections Using Foundation Models
EMNLP 2025
VinePPO: Refining Credit Assignment in RL Training of LLMs
ICML 2025
Improving Context-Aware Preference Modeling for Language Models
NeurIPS 2024
Language-guided Skill Learning with Temporal Variational Inference
ICML 2024
Towards Modular LLMs by Building and Reusing a Library of LoRAs
ICML 2024
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
NeurIPS 2023
Joint Prompt Optimization of Stacked LLMs using Variational Inference
NeurIPS 2023
Multi-Head Adapter Routing for Cross-Task Generalization
NeurIPS 2023
Target-based Surrogates for Stochastic Optimization
ICML 2023
A general class of surrogate functions for stable and efficient reinforcement learning
AISTATS 2022
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging
AISTATS 2022
Batch Reinforcement Learning Through Continuation Method
ICLR 2021
Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization
ICML 2021
Impact of Aliasing on Generalization in Deep Convolutional Networks
ICCV 2021
An operator view of policy gradient methods
NeurIPS 2020
On the interplay between noise and curvature and its effect on optimization and generalization
AISTATS 2020
A Geometric Perspective on Optimal Representations for Reinforcement Learning
NeurIPS 2019
Distributional reinforcement learning with linear function approximation
AISTATS 2019
Reducing the variance in online optimization by transporting past gradients
NeurIPS 2019
The Value Function Polytope in Reinforcement Learning
ICML 2019
Understanding the Impact of Entropy on Policy Optimization
ICML 2019
Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods
AISTATS 2018
Continuous Neural Networks
AISTATS 1999