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Tongzheng Ren

27 papers · 2018–2025 · 10 conferences · across top CS/AI conferences

Achievements

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+10 more ↓ πŸƒ Academic Marathon (7) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (10) 🐝 Cross-Pollinator (13)
🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (53) πŸ‘‘ Triple Crown πŸ† Grand Slam ⚑ Prolific Year (6) πŸ—ƒοΈ Keyword Collector (99) πŸ“ˆ Trend Setter πŸ’Ž Century Club (27) πŸ”₯ Unstoppable (8)

Conferences

NIPS (6) ICLR (5) ICML (5) UAI (3) AAAI (2) AISTATS (2) ACL (1) CVPR (1) IJCAI (1) IJCNLP (1)

Top co-authors

Bo Dai (8) Jun Zhu (7) Sujay Sanghavi (5) Dale Schuurmans (5) Tianjun Zhang (5) nhαΊ­t Hα»“ (5) Jialian Li (4) Qiang Liu (4) Chenjun Xiao (3) Khai Nguyen (3)

Research topics

Applications (1)

Keywords

regret bound (2) sample complexity (2) gradient descent (2) pre-trained transformer (2) out-of-domain detection (2) unsupervised learning (2) policy learning (2) nash equilibrium (2) latent representation (2) linear mdp (2) representation learning (2) domain generalization (2) offline reinforcement learning (1) off-policy evaluation (1) image classification (1) policy evaluation (1) probability metrics (1) one-shot learning (1) multi-task learning (1) domain adaptation (1)

Papers

Spectral Representation for Causal Estimation with Hidden Confounders AISTATS 2025 Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning ICML 2024 Improving Computational Complexity in Statistical Models with Local Curvature Information ICML 2024 Designing Robust Transformers using Robust Kernel Density Estimation NIPS 2023 Spectral Decomposition Representation for Reinforcement Learning ICLR 2023 Markovian Sliced Wasserstein Distances: Beyond Independent Projections NIPS 2023 Energy-based Predictive Representations for Partially Observed Reinforcement Learning UAI 2023 Latent Variable Representation for Reinforcement Learning ICLR 2023 Hierarchical Sliced Wasserstein Distance ICLR 2023 Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model AAAI 2022 Linear Bandit Algorithms with Sublinear Time Complexity ICML 2022 Making Linear MDPs Practical via Contrastive Representation Learning ICML 2022 Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent AISTATS 2022 A free lunch from the noise: Provable and practical exploration for representation learning UAI 2022 MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training CVPR 2021 Learning Task-Distribution Reward Shaping with Meta-Learning AAAI 2021 Unsupervised Out-of-Domain Detection via Pre-trained Transformers ACL 2021 Unsupervised Out-of-Domain Detection via Pre-trained Transformers IJCNLP 2021 Scalable Quasi-Bayesian Inference for Instrumental Variable Regression NIPS 2021 Nearly Horizon-Free Offline Reinforcement Learning NIPS 2021 Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information ICLR 2020 Implicit Regularization and Convergence for Weight Normalization NIPS 2020 Stein Self-Repulsive Dynamics: Benefits From Past Samples NIPS 2020 Accountable Off-Policy Evaluation With Kernel Bellman Statistics ICML 2020 Exploration Analysis in Finite-Horizon Turn-based Stochastic Games UAI 2020 Function Space Particle Optimization for Bayesian Neural Networks ICLR 2019 Learning to Write Stylized Chinese Characters by Reading a Handful of Examples IJCAI 2018