Tianhao Wang
34 papers · 2018–2026 · 11 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (11) π Academic Marathon (7) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (13)
π
Cross-Pollinator
(13)
π
Renaissance Researcher
(9)
πΊοΈ
Taxonomy Completionist
(50)
π
Keyword Champion
(2)
π
Triple Crown
π
Grand Slam
π₯
Mega-Team
(21)
β
The Questioner
(4)
ποΈ
Keyword Collector
(102)
π₯
Unstoppable
(5)
β‘
Prolific Year
(6)
π
Century Club
(33)
Conferences
NIPS (9)
ICLR (7)
ICML (5)
ACL (3)
AISTATS (3)
AAAI (2)
COLING (1)
EMNLP (1)
IJCNLP (1)
INTERSPEECH (1)
NSDI (1)
Top co-authors
Research topics
Keywords
reinforcement learning
(6)
regret bound
(6)
linear function approximation
(4)
stochastic mirror descent
(2)
stochastic differential equation
(2)
value iteration
(2)
machine unlearning
(2)
contextual bandit
(2)
asynchronous communication
(2)
large language model
(2)
convergence rate
(2)
bayesian inference
(1)
stochastic gradient descent
(1)
accelerated optimization
(1)
convex optimization
(1)
domain adaptation
(1)
transformer architecture
(1)
data poisoning
(1)
batch normalization
(1)
online learning
(1)
Papers
Your Reasoning Benchmark May Not Test Reasoning: Revealing Perception Bottleneck in Abstract Reasoning Benchmarks
ACL 2026
How Well Can Transformers Emulate In-Context Newtonβs Method?
AISTATS 2025
Large Language Models with Reinforcement Learning from Human Feedback Approach for Enhancing Explainable Sexism Detection
COLING 2025
Structured Preconditioners in Adaptive Optimization: A Unified Analysis
ICML 2025
Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function
ICLR 2025
Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model
ICLR 2025
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
ICLR 2025
SE/BN Adapter: Parametric Efficient Domain Adaptation for Speaker Recognition
INTERSPEECH 2024
Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
NIPS 2024
Machine Unlearning of Pre-trained Large Language Models
ACL 2024
Towards Certified Unlearning for Deep Neural Networks
ICML 2024
The Marginal Value of Momentum for Small Learning Rate SGD
ICLR 2024
Backdoor Attacks via Machine Unlearning
AAAI 2024
Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning?
ICLR 2023
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation
ICML 2023
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
NIPS 2023
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits
NIPS 2023
SRNIC: A Scalable Architecture for RDMA NICs
NSDI 2023
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning
AISTATS 2023
LAVA: Data Valuation without Pre-Specified Learning Algorithms
ICLR 2023
An Empirical Analysis of Memorization in Fine-tuned Autoregressive Language Models
EMNLP 2022
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits
NIPS 2022
Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay
NIPS 2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets
NIPS 2022
Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent
NIPS 2022
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework
ICLR 2022
Learning Stochastic Shortest Path with Linear Function Approximation
ICML 2022
Differential Privacy for Text Analytics via Natural Text Sanitization
IJCNLP 2021
Variance-Aware Off-Policy Evaluation with Linear Function Approximation
NIPS 2021
Improving Robustness to Model Inversion Attacks via Mutual Information Regularization
AAAI 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation under Adaptivity Constraints
NIPS 2021
Differential Privacy for Text Analytics via Natural Text Sanitization
ACL 2021
Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms
AISTATS 2018
Continuous and Discrete-time Accelerated Stochastic Mirror Descent for Strongly Convex Functions
ICML 2018