Tengyu Xu
17 papers · 2019–2025 · 8 conferences · across top CS/AI conferences
Achievements
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ð Cross-Pollinator (10) ð Interdisciplinary Bridge ð Conference Polyglot (8) ð Academic Marathon (6) ð Renaissance Researcher (5)
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Keyword Pioneer
ð
Interdisciplinary Bridge
ð
Conference Polyglot
(8)
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Dynamic Duo
(14)
ð
Grand Slam
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Prolific Year
(6)
ð
Century Club
(17)
ðïž
Keyword Collector
(58)
Conferences
ICLR (4)
NIPS (4)
ICML (3)
AISTATS (2)
AAAI (1)
ACL (1)
EMNLP (1)
UAI (1)
Top co-authors
Keywords
reinforcement learning
(4)
temporal difference learning
(4)
convergence analysis
(4)
stochastic approximation
(3)
markov decision process
(3)
policy gradient
(3)
off-policy learning
(3)
sample complexity
(3)
function approximation
(2)
non-asymptotic analysis
(2)
value function
(2)
convergence guarantee
(2)
natural actor-critic
(1)
inverse reinforcement learning
(1)
global convergence
(1)
policy optimization
(1)
alternating optimization
(1)
value function estimation
(1)
natural policy gradient
(1)
constraint satisfaction
(1)
Papers
Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization
ICML 2025
Learning Auxiliary Tasks Improves Reference-Free Hallucination Detection in Open-Domain Long-Form Generation
ACL 2025
Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback
EMNLP 2025
Deterministic policy gradient: Convergence analysis
UAI 2022
A Unifying Framework of Off-Policy General Value Function Evaluation
NIPS 2022
Model-Based Offline Meta-Reinforcement Learning with Regularization
ICLR 2022
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method
ICLR 2022
When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence
AISTATS 2021
CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
ICML 2021
Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality
ICML 2021
Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling
AAAI 2021
Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms
AISTATS 2021
Proximal Gradient Descent-Ascent: Variable Convergence under KÅ Geometry
ICLR 2021
Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms
NIPS 2020
Reanalysis of Variance Reduced Temporal Difference Learning
ICLR 2020
Finite-Sample Analysis for SARSA with Linear Function Approximation
NIPS 2019
Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples
NIPS 2019