Alec Koppel
26 papers · 2019–2025 · 7 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (38) π Academic Marathon Β· Sprint π£ Hot Topic Early Bird π Conference Polyglot Β· Silver
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Grand Slam
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Conference Pioneer
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Keyword Collector
(131)
Top co-authors
Research topics
Machine Learning
(21)
Reinforcement Learning
(15)
Methods
(15)
Optimization & Theory
(14)
Artificial Intelligence
(11)
Core AI
(11)
Learning Types
(9)
Mathematics & Optimization
(7)
Optimization
(7)
Deep Learning
(3)
Applications
(2)
Natural Language Processing
(1)
Architectures
(1)
Bayesian & Probabilistic
(1)
Core Methods
(1)
Keywords
reinforcement learning
(5)
sample complexity
(4)
policy gradient
(4)
multi-agent reinforcement learning
(3)
mean field game
(3)
stein discrepancy
(2)
superlinear convergence
(2)
multilevel monte carlo
(2)
hessian approximation
(2)
mixing time
(2)
continuous control
(2)
reward model
(2)
general utility
(2)
primal-dual optimization
(2)
model-based reinforcement learning
(2)
quasi-newton method
(2)
policy optimization
(2)
reinforcement learning from human feedback
(2)
stochastic gradient descent
(2)
large language model
(2)
Papers
Approximate Equivariance in Reinforcement Learning
AISTATS 2025
Collab: Controlled Decoding using Mixture of Agents for LLM Alignment
ICLR 2025
Decentralized Convergence to Equilibrium Prices in Trading Networks
AAAI 2025
GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-Time Alignment
ICLR 2025
Learning in Herding Mean Field Games: Single-Loop Algorithm with Finite-Time Convergence Analysis
AISTATS 2025
Efficient Inverse Multiagent Learning
ICLR 2024
Information-Directed Pessimism for Offline Reinforcement Learning
ICML 2024
MaxMin-RLHF: Alignment with Diverse Human Preferences
ICML 2024
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control
JMLR 2024
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback
ICLR 2024
Robust cooperative multi-agent reinforcement learning: A mean-field type game perspective
L4DC 2024
Sharpened Lazy Incremental Quasi-Newton Method
AISTATS 2024
Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles
ICML 2024
Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic
ICML 2023
Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample Path
AISTATS 2023
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning
AAAI 2023
Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities
NeurIPS 2023
STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning
ICML 2023
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach
AAAI 2022
Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic
AAAI 2022
On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces
ICML 2022
Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood
ICML 2022
A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning
JMLR 2020
Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions
L4DC 2020
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
NeurIPS 2020
Parsimonious Online Learning with Kernels via Sparse Projections in Function Space
JMLR 2019