Vladimir Braverman

Orcid: 0000-0001-7709-8753

Affiliations:
  • Johns Hopkins University


According to our database1, Vladimir Braverman authored at least 147 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of three.
  • Erdős number3 of two.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
A collective AI via lifelong learning and sharing at the edge.
Nat. Mac. Intell., 2024

Private Computations on Streaming Data.
IACR Cryptol. ePrint Arch., 2024

Federated Learning Clients Clustering with Adaptation to Data Drifts.
CoRR, 2024

Assessing and Enhancing Large Language Models in Rare Disease Question-answering.
CoRR, 2024

KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
Proceedings of the Twelfth International Conference on Learning Representations, 2024

T-Rex (Tree-Rectangles): Reformulating Decision Tree Traversal as Hyperrectangle Enclosure.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Learning-Augmented Maximum Independent Set.
Proceedings of the Approximation, 2024

Exploring the Possibility of Arrhythmia Interpretation of Time Domain ECG Using XAI: A Preliminary Study.
Proceedings of the Artificial Intelligence in Medicine - 22nd International Conference, 2024

2023
Least-Mean-Squares Coresets for Infinite Streams.
IEEE Trans. Knowl. Data Eng., September, 2023

Clustering using Approximate Nearest Neighbour Oracles.
Trans. Mach. Learn. Res., 2023

Benign Overfitting of Constant-Stepsize SGD for Linear Regression.
J. Mach. Learn. Res., 2023

ORBSLAM3-Enhanced Autonomous Toy Drones: Pioneering Indoor Exploration.
CoRR, 2023

Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing.
CoRR, 2023

A framework for dynamically training and adapting deep reinforcement learning models to different, low-compute, and continuously changing radiology deployment environments.
CoRR, 2023

Multi-environment lifelong deep reinforcement learning for medical imaging.
CoRR, 2023

Asynchronous Decentralized Federated Lifelong Learning for Landmark Localization in Medical Imaging.
CoRR, 2023

Provable Data Subset Selection For Efficient Neural Network Training.
CoRR, 2023

Learning High-Dimensional Single-Neuron ReLU Networks with Finite Samples.
CoRR, 2023

Understanding the Micro-Behaviors of Hardware Offloaded Network Stacks with Lumina.
Proceedings of the ACM SIGCOMM 2023 Conference, 2023

Private Federated Frequency Estimation: Adapting to the Hardness of the Instance.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging.
Proceedings of the Medical Imaging with Deep Learning, 2023

Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron.
Proceedings of the International Conference on Machine Learning, 2023

Provable Data Subset Selection For Efficient Neural Networks Training.
Proceedings of the International Conference on Machine Learning, 2023

AutoCoreset: An Automatic Practical Coreset Construction Framework.
Proceedings of the International Conference on Machine Learning, 2023

Lower Bounds for Pseudo-Deterministic Counting in a Stream.
Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023

Fixed Design Analysis of Regularization-Based Continual Learning.
Proceedings of the Conference on Lifelong Learning Agents, 2023

Private Data Stream Analysis for Universal Symmetric Norm Estimation.
Proceedings of the Approximation, 2023

2022
Universal Streaming of Subset Norms.
Adv. Math. Commun., 2022

Data-Independent Structured Pruning of Neural Networks via Coresets.
IEEE Trans. Neural Networks Learn. Syst., 2022

Streaming Quantiles Algorithms with Small Space and Update Time.
Sensors, 2022

From Local to Global: Spectral-Inspired Graph Neural Networks.
CoRR, 2022

Sublinear time spectral density estimation.
Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

Flow-level loss detection with Δ-sketches.
Proceedings of the SOSR '22: The ACM SIGCOMM Symposium on SDN Research, Virtual Event, October 19, 2022

The White-Box Adversarial Data Stream Model.
Proceedings of the PODS '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Pretrained Models for Multilingual Federated Learning.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Last Iterate Risk Bounds of SGD with Decaying Stepsize for Overparameterized Linear Regression.
Proceedings of the International Conference on Machine Learning, 2022

The Power of Uniform Sampling for Coresets.
Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural Activations.
Proceedings of the Conference on Lifelong Learning Agents, 2022

Gap-Dependent Unsupervised Exploration for Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

New Coresets for Projective Clustering and Applications.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Metric k-median clustering in insertion-only streams.
Discret. Appl. Math., 2021

Cross-Domain Federated Learning in Medical Imaging.
CoRR, 2021

Linear and Sublinear Time Spectral Density Estimation.
CoRR, 2021

Jaqen: A High-Performance Switch-Native Approach for Detecting and Mitigating Volumetric DDoS Attacks with Programmable Switches.
Proceedings of the 30th USENIX Security Symposium, 2021

Coresets for Clustering in Excluded-minor Graphs and Beyond.
Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms, 2021

Programmable packet scheduling with a single queue.
Proceedings of the ACM SIGCOMM 2021 Conference, Virtual Event, USA, August 23-27, 2021., 2021

Twenty Years After: Hierarchical Core-Stateless Fair Queueing.
Proceedings of the 18th USENIX Symposium on Networked Systems Design and Implementation, 2021

The Benefits of Implicit Regularization from SGD in Least Squares Problems.
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.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Coresets for Clustering with Missing Values.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarial Robustness of Streaming Algorithms through Importance Sampling.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate.
Proceedings of the 9th International Conference on Learning Representations, 2021

Near-Optimal Entrywise Sampling of Numerically Sparse Matrices.
Proceedings of the Conference on Learning Theory, 2021

Symmetric Norm Estimation and Regression on Sliding Windows.
Proceedings of the Computing and Combinatorics - 27th International Conference, 2021

Fast and memory-efficient scRNA-seq <i>k</i>-means clustering with various distances.
Proceedings of the BCB '21: 12th ACM International Conference on Bioinformatics, 2021

Lifelong Learning with Sketched Structural Regularization.
Proceedings of the Asian Conference on Machine Learning, 2021

Efficient Coreset Constructions via Sensitivity Sampling.
Proceedings of the Asian Conference on Machine Learning, 2021

2020
The one-way communication complexity of dynamic time warping distance.
J. Comput. Geom., 2020

Direction Matters: On the Implicit Regularization Effect of Stochastic Gradient Descent with Moderate Learning Rate.
CoRR, 2020

Sparse Coresets for SVD on Infinite Streams.
CoRR, 2020

NetLock: Fast, Centralized Lock Management Using Programmable Switches.
Proceedings of the SIGCOMM '20: Proceedings of the 2020 Annual conference of the ACM Special Interest Group on Data Communication on the applications, 2020

Multitask radiological modality invariant landmark localization using deep reinforcement learning.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

On the Noisy Gradient Descent that Generalizes as SGD.
Proceedings of the 37th International Conference on Machine Learning, 2020

Obtaining Adjustable Regularization for Free via Iterate Averaging.
Proceedings of the 37th International Conference on Machine Learning, 2020

FetchSGD: Communication-Efficient Federated Learning with Sketching.
Proceedings of the 37th International Conference on Machine Learning, 2020

Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension.
Proceedings of the 37th International Conference on Machine Learning, 2020

Coresets for Clustering in Graphs of Bounded Treewidth.
Proceedings of the 37th International Conference on Machine Learning, 2020

Data-Independent Neural Pruning via Coresets.
Proceedings of the 8th International Conference on Learning Representations, 2020

Near Optimal Linear Algebra in the Online and Sliding Window Models.
Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020

Sketch and Scale Geo-distributed tSNE and UMAP.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Memory-Efficient Performance Monitoring on Programmable Switches with Lean Algorithms.
Proceedings of the 1st Symposium on Algorithmic Principles of Computer Systems, 2020

2019
I Know What You Did Last Summer: Network Monitoring using Interval Queries.
Proc. ACM Meas. Anal. Comput. Syst., 2019

Multiparametric Deep Learning Tissue Signatures for Muscular Dystrophy: Preliminary Results.
CoRR, 2019

Coresets for Clustering in Graphs of Bounded Treewidth.
CoRR, 2019

On Activation Function Coresets for Network Pruning.
CoRR, 2019

DistCache: Provable Load Balancing for Large-Scale Storage Systems with Distributed Caching.
Proceedings of the 2019 USENIX Annual Technical Conference, 2019

Online Factorization and Partition of Complex Networks by Random Walk.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Nitrosketch: robust and general sketch-based monitoring in software switches.
Proceedings of the ACM Special Interest Group on Data Communication, 2019

Attack Time Localization using Interval Queries.
Proceedings of the ACM SIGCOMM 2019 Conference Posters and Demos, 2019

Communication-efficient Distributed SGD with Sketching.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Coresets for Ordered Weighted Clustering.
Proceedings of the 36th International Conference on Machine Learning, 2019

Approximations of Schatten Norms via Taylor Expansions.
Proceedings of the Computer Science - Theory and Applications, 2019

QPipe: quantiles sketch fully in the data plane.
Proceedings of the 15th International Conference on Emerging Networking Experiments And Technologies, 2019

The One-Way Communication Complexity of Dynamic Time Warping Distance.
Proceedings of the 35th International Symposium on Computational Geometry, 2019

Improved Algorithms for Time Decay Streams.
Proceedings of the Approximation, 2019

Streaming Coreset Constructions for M-Estimators.
Proceedings of the Approximation, 2019

2018
DreamNLP: Novel NLP System for Clinical Report Metadata Extraction using Count Sketch Data Streaming Algorithm: Preliminary Results.
CoRR, 2018

Scalable streaming tools for analyzing N-body simulations: Finding halos and investigating excursion sets in one pass.
Astron. Comput., 2018

New Bounds for the CLIQUE-GAP Problem Using Graph Decomposition Theory.
Algorithmica, 2018

ASAP: Fast, Approximate Graph Pattern Mining at Scale.
Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation, 2018

The Physical Systems Behind Optimization Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differentially Private Robust Low-Rank Approximation.
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.
Proceedings of the 35th International Conference on Machine Learning, 2018

Revisiting Frequency Moment Estimation in Random Order Streams.
Proceedings of the 45th International Colloquium on Automata, Languages, and Programming, 2018

Approximate Convex Hull of Data Streams.
Proceedings of the 45th International Colloquium on Automata, Languages, and Programming, 2018

Towards Fast and Scalable Graph Pattern Mining.
Proceedings of the 10th USENIX Workshop on Hot Topics in Cloud Computing, 2018

Nearly Optimal Distinct Elements and Heavy Hitters on Sliding Windows.
Proceedings of the Approximation, 2018

2017
Processing Big Data Streams (NII Shonan Meeting 2017-7).
NII Shonan Meet. Rep., 2017

Dynamic Factorization and Partition of Complex Networks.
CoRR, 2017

Streaming symmetric norms via measure concentration.
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

BPTree: An ℓ<sub>2</sub> Heavy Hitters Algorithm Using Constant Memory.
Proceedings of the 36th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2017

Clustering High Dimensional Dynamic Data Streams.
Proceedings of the 34th International Conference on Machine Learning, 2017

Accurate Low-Space Approximation of Metric k-Median for Insertion-Only Streams.
Proceedings of the Algorithms and Discrete Applied Mathematics, 2017

2016
Sliding Window Algorithms.
Encyclopedia of Algorithms, 2016

New Frameworks for Offline and Streaming Coreset Constructions.
CoRR, 2016

Sketches for Matrix Norms: Faster, Smaller and More General.
CoRR, 2016

Beating CountSketch for heavy hitters in insertion streams.
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

Clustering Problems on Sliding Windows.
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

One Sketch to Rule Them All: Rethinking Network Flow Monitoring with UnivMon.
Proceedings of the ACM SIGCOMM 2016 Conference, Florianopolis, Brazil, August 22-26, 2016, 2016

Streaming Space Complexity of Nearly All Functions of One Variable on Frequency Vectors.
Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2016

Approximating Subadditive Hadamard Functions on Implicit Matrices.
Proceedings of the Approximation, 2016

2015
Weighted sampling without replacement from data streams.
Inf. Process. Lett., 2015

A Unified Approach for Clustering Problems on Sliding Windows.
CoRR, 2015

Streaming Symmetric Norms via Measure Concentration.
CoRR, 2015

Enabling a "RISC" Approach for Software-Defined Monitoring using Universal Streaming.
Proceedings of the 14th ACM Workshop on Hot Topics in Networks, Philadelphia, PA, USA, November 16, 2015

Clustering on Sliding Windows in Polylogarithmic Space.
Proceedings of the 35th IARCS Annual Conference on Foundation of Software Technology and Theoretical Computer Science, 2015

Streaming Algorithms for Halo Finders.
Proceedings of the 11th IEEE International Conference on e-Science, 2015

Zero-One Laws for Sliding Windows and Universal Sketches.
Proceedings of the Approximation, 2015

Universal Sketches for the Frequency Negative Moments and Other Decreasing Streaming Sums.
Proceedings of the Approximation, 2015

2014
How to catch L<sub>2</sub>-heavy-hitters on sliding windows.
Theor. Comput. Sci., 2014

Universal Streaming.
CoRR, 2014

Approximating Large Frequency Moments with O(n<sup>1-2/k</sup>) Bits.
CoRR, 2014

Streaming sums in sublinear space.
CoRR, 2014

Sampling from Dense Streams without Penalty - Improved Bounds for Frequency Moments and Heavy Hitters.
Proceedings of the Computing and Combinatorics - 20th International Conference, 2014

An Optimal Algorithm for Large Frequency Moments Using O(n^(1-2/k)) Bits.
Proceedings of the Approximation, 2014

2013
How Hard Is Counting Triangles in the Streaming Model?
Proceedings of the Automata, Languages, and Programming - 40th International Colloquium, 2013

How to Catch <i>L</i> <sub>2</sub>-Heavy-Hitters on Sliding Windows.
Proceedings of the Computing and Combinatorics, 19th International Conference, 2013

Generalizing the Layering Method of Indyk and Woodruff: Recursive Sketches for Frequency-Based Vectors on Streams.
Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2013

Approximating Large Frequency Moments with Pick-and-Drop Sampling.
Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2013

2012
Optimal sampling from sliding windows.
J. Comput. Syst. Sci., 2012

2011
Streaming k-means on Well-Clusterable Data.
Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete Algorithms, 2011

2010
Effective Computations on Sliding Windows.
SIAM J. Comput., 2010

How to Catch L_2-Heavy-Hitters on Sliding Windows
CoRR, 2010

Rademacher Chaos, Random Eulerian Graphs and The Sparse Johnson-Lindenstrauss Transform
CoRR, 2010

Recursive Sketching For Frequency Moments
CoRR, 2010

Zero-one frequency laws.
Proceedings of the 42nd ACM Symposium on Theory of Computing, 2010

Measuring independence of datasets.
Proceedings of the 42nd ACM Symposium on Theory of Computing, 2010

AMS Without 4-Wise Independence on Product Domains.
Proceedings of the 27th International Symposium on Theoretical Aspects of Computer Science, 2010

2009
A linear algorithm for computing convex hulls for random lines.
ACM Trans. Algorithms, 2009

2008
Measuring $k$-Wise Independence of Streaming Data
CoRR, 2008

2007
Succinct Sampling on Streams
CoRR, 2007

Smooth Histograms for Sliding Windows.
Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2007), 2007

2006
Batched disk scheduling with delays.
SIGMETRICS Perform. Evaluation Rev., 2006


  Loading...