Cong Shen
35 papers · 2018–2025 · 10 conferences · across top CS/AI conferences
Achievements
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Conferences
AISTATS (9)
ICML (8)
NIPS (8)
ICLR (3)
EMNLP (2)
AAAI (1)
ACL (1)
IJCAI (1)
MICCAI (1)
UAI (1)
Top co-authors
Keywords
regret bound
(10)
multi-armed bandit
(8)
federated learning
(5)
upper confidence bound
(5)
in-context learning
(5)
zero-sum game
(2)
clinical trial
(2)
multi-player multi-armed bandit
(2)
safety constraint
(2)
linear bandit
(2)
markov game
(2)
decentralized learning
(2)
few-shot learning
(2)
maximum tolerated dose
(2)
best arm identification
(2)
contextual bandit
(2)
linear contextual bandit
(2)
prompt engineering
(1)
reinforcement learning
(1)
uncertainty quantification
(1)
Papers
Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis
UAI 2025
A Shared Low-Rank Adaptation Approach to Personalized RLHF
AISTATS 2025
Cost-Aware Optimal Pairwise Pure Exploration
AISTATS 2025
Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation
EMNLP 2025
From Cross-Task Examples to In-Task Prompts: A Graph-Based Pseudo-Labeling Framework for In-context Learning
EMNLP 2025
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery
ICLR 2025
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
ICLR 2025
MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning
ICML 2025
On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
ICML 2025
DCT-Net: Dual-branch CT Reconstruction from Orthogonal X-rays with Diffusion Model and Contrastive Learning
MICCAI 2025
FastGAS: Fast Graph-based Annotation Selection for In-Context Learning
ACL 2024
Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models
NIPS 2024
Federated Representation Learning in the Under-Parameterized Regime
ICML 2024
Efficient Prompt Optimization Through the Lens of Best Arm Identification
NIPS 2024
Mixture of Demonstrations for In-Context Learning
NIPS 2024
Verification of Machine Unlearning is Fragile
ICML 2024
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
AISTATS 2024
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
ICLR 2023
Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints
ICML 2023
Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources
ICML 2023
Federated Linear Bandits with Finite Adversarial Actions
NIPS 2023
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games
ICML 2022
SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups
AISTATS 2021
(Almost) Free Incentivized Exploration from Decentralized Learning Agents
NIPS 2021
Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization
NIPS 2021
Federated Linear Contextual Bandits
NIPS 2021
Federated Multi-armed Bandits with Personalization
AISTATS 2021
Federated Multi-Armed Bandits
AAAI 2021
Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty Quantification
NIPS 2020
Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints
ICML 2020
Decentralized Multi-player Multi-armed Bandits with No Collision Information
AISTATS 2020
Contextual Constrained Learning for Dose-Finding Clinical Trials
AISTATS 2020
Stochastic Linear Contextual Bandits with Diverse Contexts
AISTATS 2020
Cost-aware Cascading Bandits
IJCAI 2018
Regional Multi-Armed Bandits
AISTATS 2018