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Tongzheng Ren

According to our database¹, Tongzheng Ren authored at least 39 papers between 2018 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

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Other

Links

On csauthors.net:

Bibliography

2024

DeepSeek-VL: Towards Real-World Vision-Language Understanding.

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CoRR, 2024

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

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Mingchuan Zhang

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CoRR, 2024

2023

Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning.

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Dale Schuurmans

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CoRR, 2023

Energy-based Predictive Representations for Partially Observed Reinforcement Learning.

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Joseph E. Gonzalez

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Dale Schuurmans

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Proceedings of the Uncertainty in Artificial Intelligence, 2023

Markovian Sliced Wasserstein Distances: Beyond Independent Projections.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Designing Robust Transformers using Robust Kernel Density Estimation.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Spectral Decomposition Representation for Reinforcement Learning.

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Joseph E. Gonzalez

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Dale Schuurmans

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Proceedings of the Eleventh International Conference on Learning Representations, 2023

Latent Variable Representation for Reinforcement Learning.

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Dale Schuurmans

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Proceedings of the Eleventh International Conference on Learning Representations, 2023

Hierarchical Sliced Wasserstein Distance.

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Tan Minh Nguyen

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Proceedings of the Eleventh International Conference on Learning Representations, 2023

Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding.

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Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Robustify Transformers with Robust Kernel Density Estimation.

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Tan Minh Nguyen

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CoRR, 2022

Hierarchical Sliced Wasserstein Distance.

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CoRR, 2022

Efficient Forecasting of Large Scale Hierarchical Time Series via Multilevel Clustering.

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CoRR, 2022

Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures.

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CoRR, 2022

An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models.

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Purnamrita Sarkar

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CoRR, 2022

Improving Computational Complexity in Statistical Models with Second-Order Information.

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CoRR, 2022

A free lunch from the noise: Provable and practical exploration for representation learning.

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Csaba Szepesvári

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Proceedings of the Uncertainty in Artificial Intelligence, 2022

Making Linear MDPs Practical via Contrastive Representation Learning.

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Joseph Gonzalez

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Dale Schuurmans

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Proceedings of the International Conference on Machine Learning, 2022

Linear Bandit Algorithms with Sublinear Time Complexity.

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Sanjay Shakkottai

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Inderjit S. Dhillon

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Proceedings of the International Conference on Machine Learning, 2022

Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent.

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Alexia Atsidakou

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Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model.

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Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Combinatorial Bandits without Total Order for Arms.

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Inderjit S. Dhillon

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CoRR, 2021

Scalable Quasi-Bayesian Inference for Instrumental Variable Regression.

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Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Nearly Horizon-Free Offline Reinforcement Learning.

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Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training.

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Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Unsupervised Out-of-Domain Detection via Pre-trained Transformers.

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Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Learning Task-Distribution Reward Shaping with Meta-Learning.

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Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

MaxUp: A Simple Way to Improve Generalization of Neural Network Training.

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CoRR, 2020

Exploration Analysis in Finite-Horizon Turn-based Stochastic Games.

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Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Stein Self-Repulsive Dynamics: Benefits From Past Samples.

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Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Implicit Regularization and Convergence for Weight Normalization.

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Suriya Gunasekar

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Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Accountable Off-Policy Evaluation With Kernel Bellman Statistics.

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Proceedings of the 37th International Conference on Machine Learning, 2020

Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information.

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Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Implicit Regularization of Normalization Methods.

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Suriya Gunasekar

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CoRR, 2019

Reward Shaping via Meta-Learning.

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CoRR, 2019

Function Space Particle Optimization for Bayesian Neural Networks.

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Proceedings of the 7th International Conference on Learning Representations, 2019

Learn a Robust Policy in Adversarial Games via Playing with an Expert Opponent.

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Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Lazy-CFR: a fast regret minimization algorithm for extensive games with imperfect information.

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CoRR, 2018

Learning to Write Stylized Chinese Characters by Reading a Handful of Examples.

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Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

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