Tongzheng Ren

26 papers · 2018–2025 · 9 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🗺️ Taxonomy Completionist (62) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird

🏆 Grand Slam 👑 Triple Crown ⚡ Prolific Year · Productive 🔥 Unstoppable · Bronze 💎 Century Club · Bronze 🌈 Renaissance Researcher (6) 🗃️ Keyword Collector (136)

Venues

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

Top co-authors

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

Research topics

Machine Learning (22) Artificial Intelligence (12) Learning Types · Machine Learning (11) Optimization & Theory (11) Core AI (9) Reinforcement Learning (8) Core Methods (7) Methods (7) Deep Learning (6) Mathematics & Optimization (6) Optimization (6) Learning Types · Deep Learning (4) Application Areas (3) Learning Paradigms (3) Applications (2)

Keywords

representation learning (3) sample complexity (3) reinforcement learning (3) gradient descent (3) sliced wasserstein distance (2) optimal transport (2) policy learning (2) nash equilibrium (2) linear mdp (2) regret bound (2) policy evaluation (1) probability metrics (1) multi-task learning (1) off-policy evaluation (1) langevin dynamics (1) one-shot learning (1) robust optimization (1) domain generalization (1) sample efficiency (1) transformer architecture (1)

Papers

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