Lin Yang

According to our database, Lin Yang authored at least 112 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Federated Learning With Massive Random Access.

Shuhao Xia, Yuanming Shi, Yong Zhou, Youlong Wu, Lin F. Yang, Khaled B. Letaief

IEEE Trans. Wirel. Commun., October, 2024

Modeling Bellman-error with logistic distribution with applications in reinforcement learning.

Outongyi Lv, Bingxin Zhou, Lin F. Yang

Neural Networks, 2024

A collective AI via lifelong learning and sharing at the edge.

Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman, Eric Eaton, Benjamin Epstein, Yunhao Ge, Lucy Halperin, Jonathan P. How, Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le, Steven Lee, Xinran Liu, Sildomar T. Monteiro, David Musliner, Saptarshi Nath, Priyadarshini Panda, Christos Peridis, Hamed Pirsiavash, Vishwa S. Parekh, Kaushik Roy, Shahaf S. Shperberg, Hava T. Siegelmann, Peter Stone, Kyle Vedder, Jingfeng Wu, Lin Yang, Guangyao Zheng, Soheil Kolouri

Nat. Mac. Intell., 2024

Misspecified Q-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error.

Ally Yalei Du, Lin F. Yang, Ruosong Wang

CoRR, 2024

Confident Natural Policy Gradient for Local Planning in q_π-realizable Constrained MDPs.

Tian Tian, Lin F. Yang, Csaba Szepesvári

CoRR, 2024

Learning for Bandits under Action Erasures.

Osama A. Hanna, Merve Karakas, Lin F. Yang, Christina Fragouli

CoRR, 2024

Don't Forget to Connect! Improving RAG with Graph-based Reranking.

Jialin Dong, Bahare Fatemi, Bryan Perozzi, Lin F. Yang, Anton Tsitsulin

CoRR, 2024

Provably Correct SGD-Based Exploration for Generalized Stochastic Bandit Problem.

Jialin Dong, Jiayi Wang, Lin F. Yang

Proceedings of the International Conference on Smart Applications, 2024

Delayed MDPs with Feature Mapping.

Jialin Dong, Jiayi Wang, Lin F. Yang

Proceedings of the International Joint Conference on Neural Networks, 2024

Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation.

Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Multi-Agent Bandit Learning through Heterogeneous Action Erasure Channels.

Osama A. Hanna, Merve Karakas, Lin Yang, Christina Fragouli

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity.

Kaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang

J. Mach. Learn. Res., 2023

Adaptive Liquidity Provision in Uniswap V3 with Deep Reinforcement Learning.

Haochen Zhang, Xi Chen, Lin F. Yang

CoRR, 2023

Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing.

Sanae Amani, Khushbu Pahwa, Vladimir Braverman, Lin F. Yang

CoRR, 2023

Replicability in Reinforcement Learning.

Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou

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

Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds.

Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang

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

Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination.

Osama A. Hanna, Lin Yang, Christina Fragouli

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

Multi-Arm Bandits over Action Erasure Channels.

Osama A. Hanna, Merve Karakas, Lin F. Yang, Christina Fragouli

Proceedings of the IEEE International Symposium on Information Theory, 2023

Does Sparsity Help in Learning Misspecified Linear Bandits?

Jialin Dong, Lin Yang

Proceedings of the International Conference on Machine Learning, 2023

Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost.

Sanae Amani, Tor Lattimore, András György, Lin Yang

Proceedings of the International Conference on Machine Learning, 2023

Provably Efficient Lifelong Reinforcement Learning with Linear Representation.

Sanae Amani, Lin Yang, Ching-An Cheng

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms.

Osama A. Hanna, Lin Yang, Christina Fragouli

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

MetaVL: Transferring In-Context Learning Ability From Language Models to Vision-Language Models.

Masoud Monajatipoor, Liunian Harold Li, Mozhdeh Rouhsedaghat, Lin Yang, Kai-Wei Chang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

Compression for Multi-Arm Bandits.

Osama A. Hanna, Lin F. Yang, Christina Fragouli

IEEE J. Sel. Areas Inf. Theory, December, 2022

Universal Streaming of Subset Norms.

Vladimir Braverman, Robert Krauthgamer, Lin F. Yang

Theory Comput., 2022

Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP.

Jinghan Wang, Mengdi Wang, Lin F. Yang

CoRR, 2022

From Local to Global: Spectral-Inspired Graph Neural Networks.

Ningyuan Huang, Soledad Villar, Carey E. Priebe, Da Zheng, Chengyue Huang, Lin Yang, Vladimir Braverman

CoRR, 2022

Learning in Distributed Contextual Linear Bandits Without Sharing the Context.

Osama A. Hanna, Lin F. Yang, Christina Fragouli

CoRR, 2022

Provably Efficient Lifelong Reinforcement Learning with Linear Function Approximation.

Sanae Amani, Lin F. Yang, Ching-An Cheng

CoRR, 2022

Near-Optimal Sample Complexity Bounds for Constrained MDPs.

Sharan Vaswani, Lin Yang, Csaba Szepesvári

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning.

Dingwen Kong, Lin Yang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context.

Osama A. Hanna, Lin Yang, Christina Fragouli

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning.

Weichao Mao, Lin Yang, Kaiqing Zhang, Tamer Basar

Proceedings of the International Conference on Machine Learning, 2022

Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver.

Xiaoyu Chen, Jiachen Hu, Lin Yang, Liwei Wang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Doubly Pessimistic Algorithms for Strictly Safe Off-Policy Optimization.

Sanae Amani, Lin F. Yang

Proceedings of the 56th Annual Conference on Information Sciences and Systems, 2022

Gap-Dependent Unsupervised Exploration for Reinforcement Learning.

Jingfeng Wu, Vladimir Braverman, Lin Yang

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

Solving Multi-Arm Bandit Using a Few Bits of Communication.

Osama A. Hanna, Lin Yang, Christina Fragouli

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

2021

Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration.

Weichao Mao, Tamer Basar, Lin F. Yang, Kaiqing Zhang

CoRR, 2021

Online Sub-Sampling for Reinforcement Learning with General Function Approximation.

Dingwen Kong, Ruslan Salakhutdinov, Ruosong Wang, Lin F. Yang

CoRR, 2021

Provably Breaking the Quadratic Error Compounding Barrier in Imitation Learning, Optimally.

Nived Rajaraman, Yanjun Han, Lin F. Yang, Kannan Ramchandran, Jiantao Jiao

CoRR, 2021

A Provably Efficient Algorithm for Linear Markov Decision Process with Low Switching Cost.

Minbo Gao, Tianle Xie, Simon S. Du, Lin F. Yang

CoRR, 2021

Minimax sample complexity for turn-based stochastic game.

Qiwen Cui, Lin F. Yang

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs.

Han Zhong, Jiayi Huang, Lin Yang, Liwei Wang

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

Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning.

Jingfeng Wu, Vladimir Braverman, Lin Yang

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

On the Value of Interaction and Function Approximation in Imitation Learning.

Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran

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

Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs.

Jialin Dong, Da Zheng, Lin F. Yang, George Karypis

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Randomized Exploration in Reinforcement Learning with General Value Function Approximation.

Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang

Proceedings of the 38th International Conference on Machine Learning, 2021

Provably Correct Optimization and Exploration with Non-linear Policies.

Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang

Proceedings of the 38th International Conference on Machine Learning, 2021

Safe Reinforcement Learning with Linear Function Approximation.

Sanae Amani, Christos Thrampoulidis, Lin Yang

Proceedings of the 38th International Conference on Machine Learning, 2021

Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning.

Yuanzhi Li, Ruosong Wang, Lin F. Yang

Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

Q-learning with Logarithmic Regret.

Kunhe Yang, Lin F. Yang, Simon S. Du

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation.

Junhong Shen, Lin F. Yang

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

2020

The one-way communication complexity of dynamic time warping distance.

Vladimir Braverman, Moses Charikar, William Kuszmaul, Lin F. Yang

J. Comput. Geom., 2020

Episodic Linear Quadratic Regulators with Low-rank Transitions.

Tianyu Wang, Lin F. Yang

CoRR, 2020

Random Walk Bandits.

Tianyu Wang, Lin F. Yang, Zizhuo Wang

CoRR, 2020

Provably Efficient Reinforcement Learning with General Value Function Approximation.

Ruosong Wang, Ruslan Salakhutdinov, Lin F. Yang

CoRR, 2020

Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning?

Ruosong Wang, Simon S. Du, Lin F. Yang, Sham M. Kakade

CoRR, 2020

Provably Efficient Exploration for RL with Unsupervised Learning.

Fei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang

CoRR, 2020

Deep Reinforcement Learning with Linear Quadratic Regulator Regions.

Gabriel I. Fernandez, Colin Togashi, Dennis W. Hong, Lin F. Yang

CoRR, 2020

Preference-based Reinforcement Learning with Finite-Time Guarantees.

Yichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski

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

Planning with General Objective Functions: Going Beyond Total Rewards.

Ruosong Wang, Peilin Zhong, Simon S. Du, Ruslan Salakhutdinov, Lin F. Yang

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

Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension.

Ruosong Wang, Ruslan Salakhutdinov, Lin F. Yang

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

On Reward-Free Reinforcement Learning with Linear Function Approximation.

Ruosong Wang, Simon S. Du, Lin F. Yang, Ruslan Salakhutdinov

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

Is Long Horizon RL More Difficult Than Short Horizon RL?

Ruosong Wang, Simon S. Du, Lin F. Yang, Sham M. Kakade

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

Toward the Fundamental Limits of Imitation Learning.

Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran

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

Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning.

Fei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang

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

Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning?

Qiwen Cui, Lin F. Yang

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

Model-Based Reinforcement Learning with Value-Targeted Regression.

Zeyu Jia, Lin Yang, Csaba Szepesvári, Mengdi Wang

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound.

Lin Yang, Mengdi Wang

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

Obtaining Adjustable Regularization for Free via Iterate Averaging.

Jingfeng Wu, Vladimir Braverman, Lin Yang

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

Model-Based Reinforcement Learning with Value-Targeted Regression.

Alex Ayoub, Zeyu Jia, Csaba Szepesvári, Mengdi Wang, Lin Yang

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

Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?

Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang

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

Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal.

Alekh Agarwal, Sham M. Kakade, Lin F. Yang

Proceedings of the Conference on Learning Theory, 2020

Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity.

Aaron Sidford, Mengdi Wang, Lin Yang, Yinyu Ye

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Sketching Transformed Matrices with Applications to Natural Language Processing.

Yingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Misspecified nonconvex statistical optimization for sparse phase retrieval.

Zhuoran Yang, Lin F. Yang, Ethan X. Fang, Tuo Zhao, Zhaoran Wang, Matey Neykov

Math. Program., 2019

Does Knowledge Transfer Always Help to Learn a Better Policy?

Fei Feng, Wotao Yin, Lin F. Yang

CoRR, 2019

Continuous Control with Contexts, Provably.

Simon S. Du, Ruosong Wang, Mengdi Wang, Lin F. Yang

CoRR, 2019

On the Optimality of Sparse Model-Based Planning for Markov Decision Processes.

Alekh Agarwal, Sham M. Kakade, Lin F. Yang

CoRR, 2019

Feature-Based Q-Learning for Two-Player Stochastic Games.

Zeyu Jia, Lin F. Yang, Mengdi Wang

CoRR, 2019

Reinforcement Leaning in Feature Space: Matrix Bandit, Kernels, and Regret Bound.

Lin F. Yang, Mengdi Wang

CoRR, 2019

Sample-Optimal Parametric Q-Learning with Linear Transition Models.

Lin F. Yang, Mengdi Wang

CoRR, 2019

Online Factorization and Partition of Complex Networks by Random Walk.

Lin F. Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Efficient Symmetric Norm Regression via Linear Sketching.

Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sample-Optimal Parametric Q-Learning Using Linearly Additive Features.

Lin Yang, Mengdi Wang

Proceedings of the 36th International Conference on Machine Learning, 2019

The One-Way Communication Complexity of Dynamic Time Warping Distance.

Vladimir Braverman, Moses Charikar, William Kuszmaul, David P. Woodruff, Lin F. Yang

Proceedings of the 35th International Symposium on Computational Geometry, 2019

Learning to Control in Metric Space with Optimal Regret.

Chengzhuo Ni, Lin F. Yang, Mengdi Wang

Proceedings of the 57th Annual Allerton Conference on Communication, 2019

Towards a Theoretical Understanding of Hashing-Based Neural Nets.

Yibo Lin, Zhao Song, Lin F. Yang

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition.

Zhehui Chen, Xingguo Li, Lin Yang, Jarvis D. Haupt, Tuo Zhao

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization.

Zhehui Chen, Xingguo Li, Lin F. Yang, Jarvis D. Haupt, Tuo Zhao

CoRR, 2018

Sensitivity Sampling Over Dynamic Geometric Data Streams with Applications to k-Clustering.

Zhao Song, Lin F. Yang, Peilin Zhong

CoRR, 2018

Scalable streaming tools for analyzing N-body simulations: Finding halos and investigating excursion sets in one pass.

Nikita Ivkin, Zaoxing Liu, Lin F. Yang, S. S. Kumar, Gerard Lemson, Mark Neyrinck, Alexander S. Szalay, Vladimir Braverman, Tamas Budavari

Astron. Comput., 2018

New Bounds for the CLIQUE-GAP Problem Using Graph Decomposition Theory.

Vladimir Braverman, Zaoxing Liu, Tejasvam Singh, N. V. Vinodchandran, Lin F. Yang

Algorithmica, 2018

The Physical Systems Behind Optimization Algorithms.

Lin F. Yang, Raman Arora, Vladimir Braverman, Tuo Zhao

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model.

Aaron Sidford, Mengdi Wang, Xian Wu, Lin Yang, Yinyu Ye

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization.

Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Matrix Norms in Data Streams: Faster, Multi-Pass and Row-Order.

Vladimir Braverman, Stephen R. Chestnut, Robert Krauthgamer, Yi Li, David P. Woodruff, Lin F. Yang

Proceedings of the 35th International Conference on Machine Learning, 2018

Revisiting Frequency Moment Estimation in Random Order Streams.

Vladimir Braverman, Emanuele Viola, David P. Woodruff, Lin F. Yang

Proceedings of the 45th International Colloquium on Automata, Languages, and Programming, 2018

Approximate Convex Hull of Data Streams.

Avrim Blum, Vladimir Braverman, Ananya Kumar, Harry Lang, Lin F. Yang

Proceedings of the 45th International Colloquium on Automata, Languages, and Programming, 2018

2017

Misspecified Nonconvex Statistical Optimization for Phase Retrieval.

Zhuoran Yang, Lin F. Yang, Ethan X. Fang, Tuo Zhao, Zhaoran Wang, Matey Neykov

CoRR, 2017

Dynamic Factorization and Partition of Complex Networks.

Lin F. Yang, Vladimir Braverman, Tuo Zhao, Mengdi Wang

CoRR, 2017

On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions.

Xingguo Li, Lin F. Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao

CoRR, 2017

Streaming symmetric norms via measure concentration.

Jaroslaw Blasiok, Vladimir Braverman, Stephen R. Chestnut, Robert Krauthgamer, Lin F. Yang

Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning.

Xingguo Li, Lin Yang, Jason Ge, Jarvis D. Haupt, Tong Zhang, Tuo Zhao

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability.

Zhehui Chen, Lin F. Yang, Chris Junchi Li, Tuo Zhao

Proceedings of the 34th International Conference on Machine Learning, 2017

Clustering High Dimensional Dynamic Data Streams.

Vladimir Braverman, Gereon Frahling, Harry Lang, Christian Sohler, Lin F. Yang

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Sketches for Matrix Norms: Faster, Smaller and More General.

Vladimir Braverman, Stephen R. Chestnut, Robert Krauthgamer, Lin F. Yang

CoRR, 2016

Streaming Space Complexity of Nearly All Functions of One Variable on Frequency Vectors.

Vladimir Braverman, Stephen R. Chestnut, David P. Woodruff, Lin F. Yang

Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2016

2015

Streaming Symmetric Norms via Measure Concentration.

Vladimir Braverman, Stephen R. Chestnut, Robert Krauthgamer, Lin F. Yang

CoRR, 2015

Streaming Algorithms for Halo Finders.

Zaoxing Liu, Nikita Ivkin, Lin Yang, Mark Neyrinck, Gerard Lemson, Alexander S. Szalay, Vladimir Braverman, Tamas Budavari, Randal C. Burns, Xin Wang

Proceedings of the 11th IEEE International Conference on e-Science, 2015

2014

New Time-Space Upperbounds for Directed Reachability in High-genus and H-minor-free Graphs.

Diptarka Chakraborty, Aduri Pavan, Raghunath Tewari, N. Variyam Vinodchandran, Lin F. Yang

Electron. Colloquium Comput. Complex., 2014

2013

Mathematical Theories of Interaction with Oracles.

Lin Yang

PhD thesis, 2013