Zhao Song

Orcid: 0000-0003-4589-5234

Affiliations:
  • Adobe Research
  • Institute for Advanced Study, Princeton, NJ, USA (former)
  • Princeton University, NJ, USA (former)
  • University of Washington, DC, USA (former)
  • University of Texas at Austin, Department of Computer Science, USA (PhD 2019)
  • Harvard University, Cambridge, MA, USA (former)
  • University of California Berkeley, CA, USA (former)
  • Simon Fraser University, School of Computing Science, Burnaby, Canada (former)


According to our database1, Zhao Song authored at least 241 papers between 2012 and 2024.

Collaborative distances:

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Bibliography

2024
Unlocking the Theory Behind Scaling 1-Bit Neural Networks.
CoRR, 2024

Advancing the Understanding of Fixed Point Iterations in Deep Neural Networks: A Detailed Analytical Study.
CoRR, 2024

Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent.
CoRR, 2024

Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix.
CoRR, 2024

HSR-Enhanced Sparse Attention Acceleration.
CoRR, 2024

Fine-grained Attention I/O Complexity: Comprehensive Analysis for Backward Passes.
CoRR, 2024

Looped ReLU MLPs May Be All You Need as Practical Programmable Computers.
CoRR, 2024

Log-concave Sampling over a Convex Body with a Barrier: a Robust and Unified Dikin Walk.
CoRR, 2024

Differentially Private Kernel Density Estimation.
CoRR, 2024

Quantum Speedups for Approximating the John Ellipsoid.
CoRR, 2024

Multi-Layer Transformers Gradient Can be Approximated in Almost Linear Time.
CoRR, 2024

A Tighter Complexity Analysis of SparseGPT.
CoRR, 2024

Inverting the Leverage Score Gradient: An Efficient Approximate Newton Method.
CoRR, 2024

Fast John Ellipsoid Computation with Differential Privacy Optimization.
CoRR, 2024

Differential Privacy of Cross-Attention with Provable Guarantee.
CoRR, 2024

Differential Privacy Mechanisms in Neural Tangent Kernel Regression.
CoRR, 2024

On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs).
CoRR, 2024

Toward Infinite-Long Prefix in Transformer.
CoRR, 2024

Computational Limits of Low-Rank Adaptation (LoRA) for Transformer-Based Models.
CoRR, 2024

Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective.
CoRR, 2024

Tensor Attention Training: Provably Efficient Learning of Higher-order Transformers.
CoRR, 2024

Binary Hypothesis Testing for Softmax Models and Leverage Score Models.
CoRR, 2024

Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers.
CoRR, 2024

Exploring the Frontiers of Softmax: Provable Optimization, Applications in Diffusion Model, and Beyond.
CoRR, 2024

How to Inverting the Leverage Score Distribution?
CoRR, 2024

Attention is Naturally Sparse with Gaussian Distributed Input.
CoRR, 2024

Fourier Circuits in Neural Networks: Unlocking the Potential of Large Language Models in Mathematical Reasoning and Modular Arithmetic.
CoRR, 2024

Quantum Speedup for Spectral Approximation of Kronecker Products.
CoRR, 2024

The Fine-Grained Complexity of Gradient Computation for Training Large Language Models.
CoRR, 2024

Enhancing Stochastic Gradient Descent: A Unified Framework and Novel Acceleration Methods for Faster Convergence.
CoRR, 2024

Convex Minimization with Integer Minima in <i>Õ</i>(<i>n</i><sup>4</sup>) Time.
Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024

Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time.
Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Sublinear Adversarial Training Algorithm.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

A General Algorithm for Solving Rank-one Matrix Sensing.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Solving Attention Kernel Regression Problem via Pre-conditioner.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Fast Dynamic Sampling for Determinantal Point Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

How to Protect Copyright Data in Optimization of Large Language Models?
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Local Convergence of Approximate Newton Method for Two Layer Nonlinear Regression.
CoRR, 2023

Revisiting Quantum Algorithms for Linear Regressions: Quadratic Speedups without Data-Dependent Parameters.
CoRR, 2023

One Pass Streaming Algorithm for Super Long Token Attention Approximation in Sublinear Space.
CoRR, 2023

A Theoretical Insight into Attack and Defense of Gradient Leakage in Transformer.
CoRR, 2023

The Expressibility of Polynomial based Attention Scheme.
CoRR, 2023

Unmasking Transformers: A Theoretical Approach to Data Recovery via Attention Weights.
CoRR, 2023

Superiority of Softmax: Unveiling the Performance Edge Over Linear Attention.
CoRR, 2023

An Automatic Learning Rate Schedule Algorithm for Achieving Faster Convergence and Steeper Descent.
CoRR, 2023

Fine-tune Language Models to Approximate Unbiased In-context Learning.
CoRR, 2023

A Unified Scheme of ResNet and Softmax.
CoRR, 2023

Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network?
CoRR, 2023

A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time.
CoRR, 2023

Streaming Semidefinite Programs: O(√n) Passes, Small Space and Fast Runtime.
CoRR, 2023

Clustered Linear Contextual Bandits with Knapsacks.
CoRR, 2023

GradientCoin: A Peer-to-Peer Decentralized Large Language Models.
CoRR, 2023

Convergence of Two-Layer Regression with Nonlinear Units.
CoRR, 2023

Zero-th Order Algorithm for Softmax Attention Optimization.
CoRR, 2023

Fast Quantum Algorithm for Attention Computation.
CoRR, 2023

A Nearly-Linear Time Algorithm for Structured Support Vector Machines.
CoRR, 2023

Efficient SGD Neural Network Training via Sublinear Activated Neuron Identification.
CoRR, 2023

In-Context Learning for Attention Scheme: from Single Softmax Regression to Multiple Softmax Regression via a Tensor Trick.
CoRR, 2023

H<sub>2</sub>O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.
CoRR, 2023

Efficient Algorithm for Solving Hyperbolic Programs.
CoRR, 2023

Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation.
CoRR, 2023

Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis.
CoRR, 2023

Sparse Convolution for Approximate Sparse Instance.
CoRR, 2023

A Mathematical Abstraction for Balancing the Trade-off Between Creativity and Reality in Large Language Models.
CoRR, 2023

Faster Robust Tensor Power Method for Arbitrary Order.
CoRR, 2023

Federated Empirical Risk Minimization via Second-Order Method.
CoRR, 2023

Fast Submodular Function Maximization.
CoRR, 2023

Fast and Efficient Matching Algorithm with Deadline Instances.
CoRR, 2023

Efficient Asynchronize Stochastic Gradient Algorithm with Structured Data.
CoRR, 2023

Differentially Private Attention Computation.
CoRR, 2023

An Iterative Algorithm for Rescaled Hyperbolic Functions Regression.
CoRR, 2023

The Closeness of In-Context Learning and Weight Shifting for Softmax Regression.
CoRR, 2023

Attention Scheme Inspired Softmax Regression.
CoRR, 2023

Randomized and Deterministic Attention Sparsification Algorithms for Over-parameterized Feature Dimension.
CoRR, 2023

Convex Minimization with Integer Minima in Õ(n<sup>4</sup>) Time.
CoRR, 2023

Algorithm and Hardness for Dynamic Attention Maintenance in Large Language Models.
CoRR, 2023

An Over-parameterized Exponential Regression.
CoRR, 2023

Solving Regularized Exp, Cosh and Sinh Regression Problems.
CoRR, 2023

An Improved Sample Complexity for Rank-1 Matrix Sensing.
CoRR, 2023

A Theoretical Analysis Of Nearest Neighbor Search On Approximate Near Neighbor Graph.
CoRR, 2023

Streaming Kernel PCA Algorithm With Small Space.
CoRR, 2023

Faster Sinkhorn's Algorithm with Small Treewidth.
CoRR, 2023

Super-resolution and Robust Sparse Continuous Fourier Transform in Any Constant Dimension: Nearly Linear Time and Sample Complexity.
Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast Attention Requires Bounded Entries.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time.
Proceedings of the International Conference on Machine Learning, 2023

Federated Adversarial Learning: A Framework with Convergence Analysis.
Proceedings of the International Conference on Machine Learning, 2023

A Nearly-Optimal Bound for Fast Regression with ℓ<sub>∞</sub> Guarantee.
Proceedings of the International Conference on Machine Learning, 2023

Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability.
Proceedings of the International Conference on Machine Learning, 2023

Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance.
Proceedings of the International Conference on Machine Learning, 2023

Space-Efficient Interior Point Method, with Applications to Linear Programming and Maximum Weight Bipartite Matching.
Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023

Quartic Samples Suffice for Fourier Interpolation.
Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

Online Adaptive Mahalanobis Distance Estimation.
Proceedings of the IEEE International Conference on Big Data, 2023

Fast Heavy Inner Product Identification Between Weights and Inputs in Neural Network Training.
Proceedings of the IEEE International Conference on Big Data, 2023

Solving Tensor Low Cycle Rank Approximation.
Proceedings of the IEEE International Conference on Big Data, 2023

A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Smoothed Online Combinatorial Optimization Using Imperfect Predictions.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
An improved quantum-inspired algorithm for linear regression.
Quantum, 2022

Differentially Oblivious Relational Database Operators.
Proc. VLDB Endow., 2022

Towards Multi-Pass Streaming Lower Bounds for Optimal Approximation of Max-Cut.
Electron. Colloquium Comput. Complex., 2022

Adore: Differentially Oblivious Relational Database Operators.
CoRR, 2022

A Faster k-means++ Algorithm.
CoRR, 2022

Dynamic Kernel Sparsifiers.
CoRR, 2022

Faster Algorithm for Structured John Ellipsoid Computation.
CoRR, 2022

A Faster Small Treewidth SDP Solver.
CoRR, 2022

Discrepancy Minimization in Input-Sparsity Time.
CoRR, 2022

Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance.
CoRR, 2022

A Nearly Optimal Size Coreset Algorithm with Nearly Linear Time.
CoRR, 2022

An O(k log n) Time Fourier Set Query Algorithm.
CoRR, 2022

Training Overparametrized Neural Networks in Sublinear Time.
CoRR, 2022

Dynamic Maintenance of Kernel Density Estimation Data Structure: From Practice to Theory.
CoRR, 2022

Sublinear Time Algorithm for Online Weighted Bipartite Matching.
CoRR, 2022

Accelerating Frank-Wolfe Algorithm using Low-Dimensional and Adaptive Data Structures.
CoRR, 2022

Sparse Fourier Transform over Lattices: A Unified Approach to Signal Reconstruction.
CoRR, 2022

Speeding Up Sparsification using Inner Product Search Data Structures.
CoRR, 2022

A Dynamic Fast Gaussian Transform.
CoRR, 2022

Dynamic Tensor Product Regression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fast Distance Oracles for Any Symmetric Norm.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Symmetric Sparse Boolean Matrix Factorization and Applications.
Proceedings of the 13th Innovations in Theoretical Computer Science Conference, 2022

One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes.
Proceedings of the International Conference on Machine Learning, 2022

Bounding the Width of Neural Networks via Coupled Initialization A Worst Case Analysis.
Proceedings of the International Conference on Machine Learning, 2022

Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning.
Proceedings of the International Conference on Machine Learning, 2022

Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Solving SDP Faster: A Robust IPM Framework and Efficient Implementation.
Proceedings of the 63rd IEEE Annual Symposium on Foundations of Computer Science, 2022

Adaptive and Dynamic Multi-Resolution Hashing for Pairwise Summations.
Proceedings of the IEEE International Conference on Big Data, 2022

A Convergence Theory for Federated Average: Beyond Smoothness.
Proceedings of the IEEE International Conference on Big Data, 2022

Hyperbolic Concentration, Anti-Concentration, and Discrepancy.
Proceedings of the Approximation, 2022

Fast Graph Neural Tangent Kernel via Kronecker Sketching.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Solving Linear Programs in the Current Matrix Multiplication Time.
J. ACM, 2021

Almost Optimal Super-Constant-Pass Streaming Lower Bounds for Reachability.
Electron. Colloquium Comput. Complex., 2021

On Convergence of Federated Averaging Langevin Dynamics.
CoRR, 2021

Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes.
CoRR, 2021

An Interpretable Graph Generative Model with Heterophily.
CoRR, 2021

Scatterbrain: Unifying Sparse and Low-rank Attention Approximation.
CoRR, 2021

Sublinear Least-Squares Value Iteration via Locality Sensitive Hashing.
CoRR, 2021

FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis.
CoRR, 2021

Symmetric Boolean Factor Analysis with Applications to InstaHide.
CoRR, 2021

Solving Tall Dense SDPs in the Current Matrix Multiplication Time.
CoRR, 2021

When is particle filtering efficient for planning in partially observed linear dynamical systems?
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

A faster algorithm for solving general LPs.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Minimum cost flows, MDPs, and ℓ<sub>1</sub>-regression in nearly linear time for dense instances.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Breaking the Linear Iteration Cost Barrier for Some Well-known Conditional Gradient Methods Using MaxIP Data-structures.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Does Preprocessing Help Training Over-parameterized Neural Networks?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Evaluating Gradient Inversion Attacks and Defenses in Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scatterbrain: Unifying Sparse and Low-rank Attention.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Training (Overparametrized) Neural Networks in Near-Linear Time.
Proceedings of the 12th Innovations in Theoretical Computer Science Conference, 2021

FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis.
Proceedings of the 38th International Conference on Machine Learning, 2021

Oblivious Sketching-based Central Path Method for Linear Programming.
Proceedings of the 38th International Conference on Machine Learning, 2021

Fast Sketching of Polynomial Kernels of Polynomial Degree.
Proceedings of the 38th International Conference on Machine Learning, 2021

MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training.
Proceedings of the 9th International Conference on Learning Representations, 2021

On InstaHide, Phase Retrieval, and Sparse Matrix Factorization.
Proceedings of the 9th International Conference on Learning Representations, 2021

Near-Optimal Two-Pass Streaming Algorithm for Sampling Random Walks over Directed Graphs.
Proceedings of the 48th International Colloquium on Automata, Languages, and Programming, 2021

2020
InstaHide's Sample Complexity When Mixing Two Private Images.
CoRR, 2020

On InstaHide, Phase Retrieval, and Sparse Matrix Factorization.
CoRR, 2020

MixCon: Adjusting the Separability of Data Representations for Harder Data Recovery.
CoRR, 2020

Hyperbolic Polynomials I : Concentration and Discrepancy.
CoRR, 2020

When is Particle Filtering Efficient for POMDP Sequential Planning?
CoRR, 2020

A robust multi-dimensional sparse Fourier transform in the continuous setting.
CoRR, 2020

Average Case Column Subset Selection for Entrywise 𝓁<sub>1</sub>-Norm Loss.
CoRR, 2020

Faster Dynamic Matrix Inverse for Faster LPs.
CoRR, 2020

Privacy-preserving Learning via Deep Net Pruning.
CoRR, 2020

An improved cutting plane method for convex optimization, convex-concave games, and its applications.
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

Learning mixtures of linear regressions in subexponential time via Fourier moments.
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

Solving tall dense linear programs in nearly linear time.
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

Reducing approximate Longest Common Subsequence to approximate Edit Distance.
Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generalized Leverage Score Sampling for Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Meta-learning for Mixed Linear Regression.
Proceedings of the 37th International Conference on Machine Learning, 2020

InstaHide: Instance-hiding Schemes for Private Distributed Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

A Faster Interior Point Method for Semidefinite Programming.
Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020

Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs.
Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020

Algorithms and Hardness for Linear Algebra on Geometric Graphs.
Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020

TextHide: Tackling Data Privacy for Language Understanding Tasks.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Sketching Transformed Matrices with Applications to Natural Language Processing.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Non-Convex Matrix Completion and Related Problems via Strong Duality.
J. Mach. Learn. Res., 2019

Quadratic Suffices for Over-parametrization via Matrix Chernoff Bound.
CoRR, 2019

Efficient Model-free Reinforcement Learning in Metric Spaces.
CoRR, 2019

Stronger L2/L2 Compressed Sensing; Without Iterating.
CoRR, 2019

Four Deviations Suffice for Rank 1 Matrices.
CoRR, 2019

Stronger l<sub>2</sub>/l<sub>2</sub> compressed sensing; without iterating.
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Provable Non-linear Inductive Matrix Completion.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Average Case Column Subset Selection for Entrywise 퓁<sub>1</sub>-Norm Loss.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Towards a Zero-One Law for Column Subset Selection.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Symmetric Norm Regression via Linear Sketching.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Total Least Squares Regression in Input Sparsity Time.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Optimal Sketching for Kronecker Product Regression and Low Rank Approximation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

On the Convergence Rate of Training Recurrent Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Convergence Theory for Deep Learning via Over-Parameterization.
Proceedings of the 36th International Conference on Machine Learning, 2019

The Limitations of Adversarial Training and the Blind-Spot Attack.
Proceedings of the 7th International Conference on Learning Representations, 2019

Approximation Algorithms for LCS and LIS with Truly Improved Running Times.
Proceedings of the 60th IEEE Annual Symposium on Foundations of Computer Science, 2019

(Nearly) Sample-Optimal Sparse Fourier Transform in Any Dimension; RIPless and Filterless.
Proceedings of the 60th IEEE Annual Symposium on Foundations of Computer Science, 2019

Solving Empirical Risk Minimization in the Current Matrix Multiplication Time.
Proceedings of the Conference on Learning Theory, 2019

Towards a Theoretical Understanding of Hashing-Based Neural Nets.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Topic Modeling in Online Social Media, User Features and Social Networks for.
Proceedings of the Encyclopedia of Social Network Analysis and Mining, 2nd Edition, 2018

Optimizing squares covering a set of points.
Theor. Comput. Sci., 2018

Relative Error Tensor Low Rank Approximation.
Electron. Colloquium Comput. Complex., 2018

Algorithmic Theory of ODEs and Sampling from Well-conditioned Logconcave Densities.
CoRR, 2018

Towards a Zero-One Law for Entrywise Low Rank Approximation.
CoRR, 2018

Nonlinear Inductive Matrix Completion based on One-layer Neural Networks.
CoRR, 2018

Sensitivity Sampling Over Dynamic Geometric Data Streams with Applications to k-Clustering.
CoRR, 2018

A matrix expander Chernoff bound.
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018

Learning Long Term Dependencies via Fourier Recurrent Units.
Proceedings of the 35th International Conference on Machine Learning, 2018

Towards Fast Computation of Certified Robustness for ReLU Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

A Matrix Chernoff Bound for Strongly Rayleigh Distributions and Spectral Sparsifiers from a few Random Spanning Trees.
Proceedings of the 59th IEEE Annual Symposium on Foundations of Computer Science, 2018

Parallel Graph Connectivity in Log Diameter Rounds.
Proceedings of the 59th IEEE Annual Symposium on Foundations of Computer Science, 2018

Stochastic Multi-armed Bandits in Constant Space.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Sketching for Kronecker Product Regression and P-splines.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Learning Non-overlapping Convolutional Neural Networks with Multiple Kernels.
CoRR, 2017

Fast Regression with an $\ell_\infty$ Guarantee.
CoRR, 2017

Low rank approximation with entrywise l<sub>1</sub>-norm error.
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017

Recovery Guarantees for One-hidden-layer Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Fast Regression with an $ell_infty$ Guarantee.
Proceedings of the 44th International Colloquium on Automata, Languages, and Programming, 2017

2016
The p-Center Problem in Tree Networks Revisited.
Proceedings of the 15th Scandinavian Symposium and Workshops on Algorithm Theory, 2016

Weighted low rank approximations with provable guarantees.
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

Sublinear Time Orthogonal Tensor Decomposition.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Maximum Sustainable Yield Problem for Robot Foraging and Construction System.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Fourier-Sparse Interpolation without a Frequency Gap.
Proceedings of the IEEE 57th Annual Symposium on Foundations of Computer Science, 2016

2015
Minmax regret 1-center algorithms for path/tree/unicycle/cactus networks.
Discret. Appl. Math., 2015

A Robust Sparse Fourier Transform in the Continuous Setting.
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

Novel power grid reduction method based on L1 regularization.
Proceedings of the 52nd Annual Design Automation Conference, 2015

Global Policy Construction in Modular Reinforcement Learning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Topic Modeling in Online Social Media, User Features, and Social Networks for.
Encyclopedia of Social Network Analysis and Mining, 2014

Batch Codes through Dense Graphs without Short Cycles.
Electron. Colloquium Comput. Complex., 2014

A Linear Time Algorithm for Computing Minmax Regret 1-Median on a Tree Network.
Algorithmica, 2014

Improved Minmax Regret 1-Center Algorithms for Cactus Networks with c Cycles.
Proceedings of the LATIN 2014: Theoretical Informatics - 11th Latin American Symposium, Montevideo, Uruguay, March 31, 2014

Back-Up 2-Center on a Path/Tree/Cycle/Unicycle.
Proceedings of the Computing and Combinatorics - 20th International Conference, 2014

Optimizing Squares Covering a Set of Points.
Proceedings of the Combinatorial Optimization and Applications, 2014

Probabilistic recharging model in uncertain environments.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

2013
Sustainable robot foraging: Adaptive fine-grained multi-robot task allocation for maximum sustainable yield of biological resources.
Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013

Graphical Model-Based Learning in High Dimensional Feature Spaces.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012
Computing Minmax Regret 1-Median on a Tree Network with Positive/Negative Vertex Weights.
Proceedings of the Algorithms and Computation - 23rd International Symposium, 2012

User Features and Social Networks for Topic Modeling in Online Social Media.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2012

MO-LOST: adaptive ant trail untangling in multi-objective multi-colony robot foraging.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012


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