Vladimir Braverman
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
75
Venues
30
Active years
2007–2026
Best venue rank
A*
Where they publish
- A*ICML15 papers
- A*SIGCOMM7 papers
- A*STOC5 papers
- A*SODA4 papers
- A*FOCS4 papers
- A*ICALP4 papers
- A*PODS4 papers
- AAISTATS3 papers
- A*ICLR3 papers
- NationalCOCOON3 papers
- A*ACL2 papers
- CACML2 papers
- A*COLT2 papers
- AEACL1 paper
- A*EMNLP1 paper
- A*ICCV1 paper
- BAIME1 paper
- A*ICDE1 paper
- ANAACL1 paper
- NationalNSDI1 paper
- A*SIGMETRICS1 paper
- ACoNEXT1 paper
- NationalCSR1 paper
- AFAST1 paper
- AUAI1 paper
- AUSENIX1 paper
- A*OSDI1 paper
- NationalHOTNETS1 paper
- BMFCS1 paper
- ASTACS1 paper
Papers
75 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | AutoL2S: Auto Long-Short Reasoning for Efficient Large Language Models. | Feng Luo, Yu-Neng Chuang, Guanchu Wang, Hoang Anh Duy Le, Shaochen Zhong, Hongyi Liu, Jiayi Yuan, Yang Sui, Vladimir Braverman, Vipin Chaudhary, Xia Ben Hu |
| 2026 | EACL | FaithLM: Towards Faithful Explanations for Large Language Models. | Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Ruixiang Tang, Shaochen Zhong, Fan Yang, Andrew Wen, Mengnan Du, Xuanting Cai, Vladimir Braverman, Xia Hu |
| 2026 | SODA | Online Learning with Limited Information in the Sliding Window Model. | Vladimir Braverman, Sumegha Garg, Chen Wang, David P. Woodruff, Samson Zhou |
| 2026 | SIGCOMM | Poster: Improving Resource Usage with Self-MeNDing Sketches. | Jonathan Diamant, Shir Landau Feibish, Zaoxing Liu, Vladimir Braverman |
| 2025 | ACL | CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems. | Haochen Zhang, Tianyi Zhang, Junze Yin, Oren Gal, Anshumali Shrivastava, Vladimir Braverman |
| 2025 | AISTATS | Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time. | Vladimir Braverman, Prathamesh Dharangutte, Shreyas Pai, Vihan Shah, Chen Wang |
| 2025 | EMNLP | Self-Ensemble: Mitigating Confidence Distortion for Large Language Models. | Zicheng Xu, Guanchu Wang, Guangyao Zheng, Yu-Neng Chuang, Alex Szalay, Xia Hu, Vladimir Braverman |
| 2025 | FOCS | Adversarially Robust Quantum State Learning and Testing. | Maryam Aliakbarpour, Vladimir Braverman, Nai-Hui Chia, Yuhan Liu |
| 2025 | ICCV | Generative Counterfactual Augmentation for Bias Mitigation. | Jason Uwaeze, Pranav Kulkarni, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh |
| 2025 | ICML | Relative Error Fair Clustering in the Weak-Strong Oracle Model. | Vladimir Braverman, Prathamesh Dharangutte, Shaofeng H.-C. Jiang, Hoai-An Nguyen, Chen Wang, Yubo Zhang, Samson Zhou |
| 2025 | ICML | Learning-Augmented Hierarchical Clustering. | Vladimir Braverman, Jon C. Ergun, Chen Wang, Samson Zhou |
| 2024 | AIME | Exploring the Possibility of Arrhythmia Interpretation of Time Domain ECG Using XAI: A Preliminary Study. | Sunghan Lee, Jeonghwan Koh, Guangyao Zheng, Vladimir Braverman, In Cheol Jeong |
| 2024 | ICDE | T-Rex (Tree-Rectangles): Reformulating Decision Tree Traversal as Hyperrectangle Enclosure. | Meghana Madhyastha, Tamas Budavari, Vladimir Braverman, Joshua T. Vogelstein, Randal C. Burns |
| 2024 | ICLR | How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression? | Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Peter L. Bartlett |
| 2024 | ICML | KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache. | Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen (Henry) Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, Xia Hu |
| 2023 | ICALP | Lower Bounds for Pseudo-Deterministic Counting in a Stream. | Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan, Shay Sapir |
| 2023 | ICML | AutoCoreset: An Automatic Practical Coreset Construction Framework. | Alaa Maalouf, Murad Tukan, Vladimir Braverman, Daniela Rus |
| 2023 | ICML | Provable Data Subset Selection For Efficient Neural Networks Training. | Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman |
| 2023 | ICML | Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron. | Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Sham M. Kakade |
| 2023 | SIGCOMM | Understanding the Micro-Behaviors of Hardware Offloaded Network Stacks with Lumina. | Zhuolong Yu, Bowen Su, Wei Bai, Shachar Raindel, Vladimir Braverman, Xin Jin |
| 2022 | AISTATS | New Coresets for Projective Clustering and Applications. | Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman |
| 2022 | AISTATS | Gap-Dependent Unsupervised Exploration for Reinforcement Learning. | Jingfeng Wu, Vladimir Braverman, Lin Yang |
| 2022 | FOCS | The Power of Uniform Sampling for Coresets. | Vladimir Braverman, Vincent Cohen-Addad, Shaofeng H.-C. Jiang, Robert Krauthgamer, Chris Schwiegelshohn, Mads Bech Toftrup, Xuan Wu |
| 2022 | ICML | Last Iterate Risk Bounds of SGD with Decaying Stepsize for Overparameterized Linear Regression. | Jingfeng Wu, Difan Zou, Vladimir Braverman, Quanquan Gu, Sham M. Kakade |
| 2022 | NAACL | Pretrained Models for Multilingual Federated Learning. | Orion Weller, Marc Marone, Vladimir Braverman, Dawn J. Lawrie, Benjamin Van Durme |
| 2022 | PODS | The White-Box Adversarial Data Stream Model. | Mikls Ajtai, Vladimir Braverman, T. S. Jayram, Sandeep Silwal, Alec Sun, David P. Woodruff, Samson Zhou |
| 2022 | STOC | Sublinear time spectral density estimation. | Vladimir Braverman, Aditya Krishnan, Christopher Musco |
| 2021 | ACML | Efficient Coreset Constructions via Sensitivity Sampling. | Vladimir Braverman, Dan Feldman, Harry Lang, Adiel Statman, Samson Zhou |
| 2021 | ACML | Lifelong Learning with Sketched Structural Regularization. | Haoran Li, Aditya Krishnan, Jingfeng Wu, Soheil Kolouri, Praveen K. Pilly, Vladimir Braverman |
| 2021 | COCOON | Symmetric Norm Estimation and Regression on Sliding Windows. | Vladimir Braverman, Viska Wei, Samson Zhou |
| 2021 | COLT | Near-Optimal Entrywise Sampling of Numerically Sparse Matrices. | Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan, Shay Sapir |
| 2021 | COLT | Benign Overfitting of Constant-Stepsize SGD for Linear Regression. | Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Sham M. Kakade |
| 2021 | ICLR | Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate. | Jingfeng Wu, Difan Zou, Vladimir Braverman, Quanquan Gu |
| 2021 | NSDI | Twenty Years After: Hierarchical Core-Stateless Fair Queueing. | Zhuolong Yu, Jingfeng Wu, Vladimir Braverman, Ion Stoica, Xin Jin |
| 2021 | SODA | Coresets for Clustering in Excluded-minor Graphs and Beyond. | Vladimir Braverman, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu |
| 2021 | SIGCOMM | Programmable packet scheduling with a single queue. | Zhuolong Yu, Chuheng Hu, Jingfeng Wu, Xiao Sun, Vladimir Braverman, Mosharaf Chowdhury, Zhenhua Liu, Xin Jin |
| 2020 | FOCS | Near Optimal Linear Algebra in the Online and Sliding Window Models. | Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou |
| 2020 | ICLR | Data-Independent Neural Pruning via Coresets. | Ben Mussay, Margarita Osadchy, Vladimir Braverman, Samson Zhou, Dan Feldman |
| 2020 | ICML | Coresets for Clustering in Graphs of Bounded Treewidth. | Daniel N. Baker, Vladimir Braverman, Lingxiao Huang, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu |
| 2020 | ICML | Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension. | Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan, Roi Sinoff |
| 2020 | ICML | FetchSGD: Communication-Efficient Federated Learning with Sketching. | Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora |
| 2020 | ICML | Obtaining Adjustable Regularization for Free via Iterate Averaging. | Jingfeng Wu, Vladimir Braverman, Lin Yang |
| 2020 | ICML | On the Noisy Gradient Descent that Generalizes as SGD. | Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Vladimir Braverman, Zhanxing Zhu |
| 2020 | SIGCOMM | NetLock: Fast, Centralized Lock Management Using Programmable Switches. | Zhuolong Yu, Yiwen Zhang, Vladimir Braverman, Mosharaf Chowdhury, Xin Jin |
| 2020 | SIGMETRICS | I Know What You Did Last Summer: Network Monitoring using Interval Queries. | Nikita Ivkin, Ran Ben Basat, Zaoxing Liu, Gil Einziger, Roy Friedman, Vladimir Braverman |
| 2019 | CoNEXT | QPipe: quantiles sketch fully in the data plane. | Nikita Ivkin, Zhuolong Yu, Vladimir Braverman, Xin Jin |
| 2019 | CSR | Approximations of Schatten Norms via Taylor Expansions. | Vladimir Braverman |
| 2019 | FAST | DistCache: Provable Load Balancing for Large-Scale Storage Systems with Distributed Caching. | Zaoxing Liu, Zhihao Bai, Zhenming Liu, Xiaozhou Li, Changhoon Kim, Vladimir Braverman, Xin Jin, Ion Stoica |
| 2019 | ICML | Coresets for Ordered Weighted Clustering. | Vladimir Braverman, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu |
| 2019 | UAI | Online Factorization and Partition of Complex Networks by Random Walk. | Lin F. Yang, Zheng Yu, Vladimir Braverman, Tuo Zhao, Mengdi Wang |
| 2019 | SIGCOMM | Attack Time Localization using Interval Queries. | Nikita Ivkin, Ran Ben Basat, Zaoxing Liu, Gil Einziger, Roy Friedman, Vladimir Braverman |
| 2019 | SIGCOMM | Nitrosketch: robust and general sketch-based monitoring in software switches. | Zaoxing Liu, Ran Ben-Basat, Gil Einziger, Yaron Kassner, Vladimir Braverman, Roy Friedman, Vyas Sekar |
| 2019 | USENIX | DistCache: Provable Load Balancing for Large-Scale Storage Systems with Distributed Caching. | Zaoxing Liu, Zhihao Bai, Zhenming Liu, Xiaozhou Li, Changhoon Kim, Vladimir Braverman, Xin Jin, Ion Stoica |
| 2018 | ICALP | Approximate Convex Hull of Data Streams. | Avrim Blum, Vladimir Braverman, Ananya Kumar, Harry Lang, Lin F. Yang |
| 2018 | ICALP | Revisiting Frequency Moment Estimation in Random Order Streams. | Vladimir Braverman, Emanuele Viola, David P. Woodruff, Lin F. Yang |
| 2018 | ICML | 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 |
| 2018 | OSDI | ASAP: Fast, Approximate Graph Pattern Mining at Scale. | Anand Padmanabha Iyer, Zaoxing Liu, Xin Jin, Shivaram Venkataraman, Vladimir Braverman, Ion Stoica |
| 2017 | ICML | Clustering High Dimensional Dynamic Data Streams. | Vladimir Braverman, Gereon Frahling, Harry Lang, Christian Sohler, Lin F. Yang |
| 2017 | PODS | BPTree: An ℓ | Vladimir Braverman, Stephen R. Chestnut, Nikita Ivkin, Jelani Nelson, Zhengyu Wang, David P. Woodruff |
| 2017 | STOC | Streaming symmetric norms via measure concentration. | Jaroslaw Blasiok, Vladimir Braverman, Stephen R. Chestnut, Robert Krauthgamer, Lin F. Yang |
| 2016 | PODS | Streaming Space Complexity of Nearly All Functions of One Variable on Frequency Vectors. | Vladimir Braverman, Stephen R. Chestnut, David P. Woodruff, Lin F. Yang |
| 2016 | SODA | Clustering Problems on Sliding Windows. | Vladimir Braverman, Harry Lang, Keith D. Levin, Morteza Monemizadeh |
| 2016 | STOC | Beating CountSketch for heavy hitters in insertion streams. | Vladimir Braverman, Stephen R. Chestnut, Nikita Ivkin, David P. Woodruff |
| 2016 | SIGCOMM | One Sketch to Rule Them All: Rethinking Network Flow Monitoring with UnivMon. | Zaoxing Liu, Antonis Manousis, Gregory Vorsanger, Vyas Sekar, Vladimir Braverman |
| 2015 | HOTNETS | Enabling a "RISC" Approach for Software-Defined Monitoring using Universal Streaming. | Zaoxing Liu, Gregory Vorsanger, Vladimir Braverman, Vyas Sekar |
| 2015 | MFCS | New Bounds for the CLIQUE-GAP Problem Using Graph Decomposition Theory. | Vladimir Braverman, Zaoxing Liu, Tejasvam Singh, N. V. Vinodchandran, Lin F. Yang |
| 2014 | COCOON | Sampling from Dense Streams without Penalty - Improved Bounds for Frequency Moments and Heavy Hitters. | Vladimir Braverman, Gregory Vorsanger |
| 2013 | COCOON | How to Catch | Vladimir Braverman, Ran Gelles, Rafail Ostrovsky |
| 2013 | ICALP | How Hard Is Counting Triangles in the Streaming Model? | Vladimir Braverman, Rafail Ostrovsky, Dan Vilenchik |
| 2011 | SODA | Streaming k-means on Well-Clusterable Data. | Vladimir Braverman, Adam Meyerson, Rafail Ostrovsky, Alan Roytman, Michael Shindler, Brian Tagiku |
| 2010 | STOC | Measuring independence of datasets. | Vladimir Braverman, Rafail Ostrovsky |
| 2010 | STOC | Zero-one frequency laws. | Vladimir Braverman, Rafail Ostrovsky |
| 2010 | STACS | AMS Without 4-Wise Independence on Product Domains. | Vladimir Braverman, Kai-Min Chung, Zhenming Liu, Michael Mitzenmacher, Rafail Ostrovsky |
| 2009 | PODS | Optimal sampling from sliding windows. | Vladimir Braverman, Rafail Ostrovsky, Carlo Zaniolo |
| 2007 | FOCS | Smooth Histograms for Sliding Windows. | Vladimir Braverman, Rafail Ostrovsky |