Kunal Talwar
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Kunal Talwarcomputer-science Degrees
Computer Science
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Machine Learning
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Computer Science
Kunal Talwar's Degrees
- PhD Computer Science Stanford University
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(Suggest an Edit or Addition)Kunal Talwar's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (2016) (9876)
- Deep Learning with Differential Privacy (2016) (3519)
- Mechanism Design via Differential Privacy (2007) (2002)
- Quincy: fair scheduling for distributed computing clusters (2009) (953)
- A tight bound on approximating arbitrary metrics by tree metrics (2003) (892)
- Learning Differentially Private Recurrent Language Models (2017) (783)
- Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (2016) (746)
- The complexity of pure Nash equilibria (2004) (661)
- Adversarially Robust Generalization Requires More Data (2018) (624)
- Privacy, accuracy, and consistency too: a holistic solution to contingency table release (2007) (503)
- Detecting Format String Vulnerabilities with Type Qualifiers (2001) (442)
- Scalable Private Learning with PATE (2018) (401)
- On the geometry of differential privacy (2009) (401)
- Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity (2018) (283)
- An approximate truthful mechanism for combinatorial auctions with single parameter agents (2003) (267)
- Heuristics for Vector Bin Packing (2011) (236)
- The price of privacy and the limits of LP decoding (2007) (229)
- Analyze gauss: optimal bounds for privacy-preserving principal component analysis (2014) (222)
- Bypassing the embedding: algorithms for low dimensional metrics (2004) (204)
- Differentially private combinatorial optimization (2009) (185)
- Constrained Non-monotone Submodular Maximization: Offline and Secretary Algorithms (2010) (178)
- The Limits of Two-Party Differential Privacy (2010) (178)
- Paths, trees, and minimum latency tours (2003) (177)
- The geometry of differential privacy: the sparse and approximate cases (2012) (175)
- Private Stochastic Convex Optimization with Optimal Rates (2019) (148)
- Rényi Differential Privacy of the Sampled Gaussian Mechanism (2019) (134)
- Validating Heuristics for Virtual Machines Consolidation (2011) (132)
- Click Fraud Resistant Methods for Learning Click-Through Rates (2005) (126)
- Nearly Optimal Private LASSO (2015) (124)
- Private stochastic convex optimization: optimal rates in linear time (2020) (123)
- Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses (2020) (120)
- Online Linear Quadratic Control (2018) (113)
- Better Algorithms for Stochastic Bandits with Adversarial Corruptions (2019) (109)
- On differentially private low rank approximation (2013) (108)
- Privacy Amplification by Iteration (2018) (108)
- Learning Differentially Private Language Models Without Losing Accuracy (2017) (96)
- The Price of Truth: Frugality in Truthful Mechanisms (2003) (92)
- Consistent Weighted Sampling (2007) (90)
- Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling (2020) (88)
- Secretary problems: weights and discounts (2009) (82)
- The Single-Sink Buy-at-Bulk LP Has Constant Integrality Gap (2002) (81)
- Private selection from private candidates (2018) (80)
- Efficient distributed approximation algorithms via probabilistic tree embeddings (2008) (77)
- Lower Bounds on Near Neighbor Search via Metric Expansion (2010) (73)
- Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation (2020) (70)
- Vertex Sparsifiers: New Results from Old Techniques (2010) (69)
- An improved approximation algorithm for the 0-extension problem (2003) (62)
- Inapproximability of Edge-Disjoint Paths and low congestion routing on undirected graphs (2010) (61)
- An Improved Decomposition Theorem for Graphs Excluding a Fixed Minor (2003) (60)
- Semi-Cyclic Stochastic Gradient Descent (2019) (59)
- Approximating unique games (2006) (57)
- Approximate classification via earthmover metrics (2004) (56)
- Balanced allocations: the weighted case (2007) (52)
- The (1 + β)-choice process and weighted balls-into-bins (2010) (48)
- Private Empirical Risk Minimization Beyond the Worst Case: The Effect of the Constraint Set Geometry (2014) (48)
- Navigation made personal: inferring driving preferences from GPS traces (2015) (47)
- Cops, robbers, and threatening skeletons: padded decomposition for minor-free graphs (2013) (47)
- Unconditional differentially private mechanisms for linear queries (2012) (47)
- On the Protection of Private Information in Machine Learning Systems: Two Recent Approches (2017) (46)
- Efficient Algorithms for Privately Releasing Marginals via Convex Relaxations (2013) (46)
- When is memorization of irrelevant training data necessary for high-accuracy learning? (2020) (45)
- Private Stochastic Convex Optimization: Optimal Rates in 𝓁1 Geometry (2021) (44)
- Characterizing Structural Regularities of Labeled Data in Overparameterized Models (2020) (43)
- Hardness of routing with congestion in directed graphs (2007) (43)
- Reconstructing approximate tree metrics (2007) (42)
- A Geometric Approach to Lower Bounds for Approximate Near-Neighbor Search and Partial Match (2008) (41)
- Changing Bases: Multistage Optimization for Matroids and Matchings (2014) (40)
- Graphical balanced allocations and the (1 + β)‐choice process (2015) (36)
- Balanced Allocations: A Simple Proof for the Heavily Loaded Case (2013) (36)
- Factorization Norms and Hereditary Discrepancy (2014) (34)
- Sparsest cut on bounded treewidth graphs: algorithms and hardness results (2013) (34)
- What Would Edmonds Do? Augmenting Paths and Witnesses for Degree-Bounded MSTs (2009) (33)
- Consistent Weighted Sampling Made Fast, Small, and Easy (2014) (32)
- Fully Dynamic All-Pairs Shortest Paths: Breaking the O(n) Barrier (2014) (31)
- On the Utility of Privacy-Preserving Histograms (2004) (29)
- On Privacy-Preserving Histograms (2005) (29)
- A Constant Approximation Algorithm for the a prioriTraveling Salesman Problem (2008) (29)
- Private Adaptive Gradient Methods for Convex Optimization (2021) (29)
- Approximating the Bandwidth of Caterpillars (2005) (25)
- Differentially Private Approximation Algorithms (2009) (25)
- Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC (2020) (24)
- Online learning over a finite action set with limited switching (2018) (24)
- The Geometry of Differential Privacy: The Small Database and Approximate Cases (2016) (24)
- A Push-Relabel Algorithm for Approximating Degree Bounded MSTs (2006) (19)
- Improving Integrality Gaps via Chvátal-Gomory Rounding (2010) (19)
- Smooth Boolean Functions are Easy: Efficient Algorithms for Low-Sensitivity Functions (2015) (19)
- Approximating Hereditary Discrepancy via Small Width Ellipsoids (2013) (19)
- Bypassing the Embedding: Approximation schemes and Compact Representations for Low Dimensional Metrics (2004) (18)
- Using Convex Relaxations for Efficiently and Privately Releasing Marginals (2014) (18)
- Lossless Compression of Efficient Private Local Randomizers (2021) (17)
- A primal-dual algorithm for computing Fisher equilibrium in the absence of gross substitutability property (2005) (16)
- A push-relabel approximation algorithm for approximating the minimum-degree MST problem and its generalization to matroids (2009) (16)
- The Apple PSI System (2021) (15)
- The Complexity of Pure Nash Equilibria (Extended Abstract) (2004) (13)
- Approximating metrics by tree metrics (2004) (13)
- What Would Edmonds Do? Augmenting Paths and Witnesses for Degree-Bounded MSTs (2005) (13)
- Balancing Vectors in Any Norm (2018) (13)
- Ultra-low-dimensional embeddings for doubling metrics (2008) (13)
- Minimum Makespan Scheduling with Low Rank Processing Times (2013) (12)
- Virtual Ring Routing Trends (2009) (11)
- Computational Separations between Sampling and Optimization (2019) (11)
- LAST but not Least: Online Spanners for Buy-at-Bulk (2016) (11)
- Optimal Algorithms for Mean Estimation under Local Differential Privacy (2022) (11)
- Exploring the Memorization-Generalization Continuum in Deep Learning (2020) (11)
- Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss (2022) (11)
- Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy (2022) (10)
- Hardness of Low Congestion Routing in Directed Graphs (2006) (10)
- The Generalized Deadlock Resolution Problem (2005) (10)
- Stochastic Optimization with Laggard Data Pipelines (2020) (9)
- Sketching and Neural Networks (2016) (9)
- Balloon Popping With Applications to Ascending Auctions (2007) (9)
- On The Hereditary Discrepancy of Homogeneous Arithmetic Progressions (2013) (8)
- Hard Instances for Satisfiability and Quasi-one-way Functions (2010) (8)
- Mean Estimation with User-level Privacy under Data Heterogeneity (2022) (7)
- Non-Uniform Graph Partitioning (2014) (7)
- Random Sampling Auctions for Limited Supply (2007) (7)
- Analyze Gauss: optimal bounds for privacy-preserving PCA (2014) (6)
- The (1 + beta)-Choice Process and Weighted Balls-into-Bins (2010) (6)
- Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling (2022) (6)
- Private Frequency Estimation via Projective Geometry (2022) (5)
- DLVM : A MODERN COMPILER INFRASTRUCTURE FOR DEEP LEARNING (2017) (4)
- Random Rates for 0-Extension and Low-Diameter Decompositions (2013) (4)
- A ug 2 01 7 On the Protection of Private Information in Machine Learning Systems : Two Recent Approaches ( Invited Paper ) (2018) (4)
- Short and Deep: Sketching and Neural Networks (2017) (3)
- Approximating Metric Spaces by Tree Metrics (2008) (3)
- Making Doubling Metrics Geodesic (2010) (3)
- Private Online Prediction from Experts: Separations and Faster Rates (2022) (3)
- How to Complete a Doubling Metric (2007) (2)
- Learning Representations for Faster Similarity Search (2018) (2)
- On the Error Resistance of Hinge Loss Minimization (2020) (2)
- Approximating Discrepancy via Small Width Ellipsoids (2014) (2)
- Oblivious Stash Shuffle (2017) (2)
- Tabular data protection DIFFERENTIALLY PRIVATE MARGINALS RELEASE WITH MUTUAL CONSISTENCY AND ERROR INDEPENDENT OF SAMPLE SIZE (2007) (2)
- Practical Almost-Linear-Time Approximation Algorithms for Hybrid and Overlapping Graph Clustering (2022) (2)
- Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation (2022) (2)
- FLAIR: Federated Learning Annotated Image Repository (2022) (1)
- Lecture Notes for the 26th Mcgill Invitational Workshop on Computational Complexity (2016) (1)
- Concentration of the Langevin Algorithm's Stationary Distribution (2022) (1)
- Hereditary discrepancy and factorization norms organized by (2017) (0)
- A Simple Characterization for Truth-Revealing Single-Item Auctions (2005) (0)
- Approximation Algorithms (2014) (0)
- TensorFlow Distributions Joshua (2017) (0)
- Metric methods in approximation algorithms (2004) (0)
- Practical Nearly-Linear-Time Approximation Algorithms for Hybrid and Overlapping Graph Clustering (2022) (0)
- Ju l 2 01 4 Approximating Hereditary Discrepancy via Small Width Ellipsoids (2014) (0)
- Fast solver for large systems of linear equations (2000) (0)
- Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime (2023) (0)
- Efficient Algorithms for Privately Releasing Marginals via Convex Relaxations (2015) (0)
- Subspace Recovery from Heterogeneous Data with Non-isotropic Noise (2022) (0)
- Private Federated Statistics in an Interactive Setting (2022) (0)
- Amplification Theorems for Differentially Private Machine Learning (2019) (0)
- Neural Guidance for SAT Solving (2018) (0)
- PRIVATE SELECTION FROM PRIVATE CANDIDATES JINGCHENG LIU AND KUNAL TALWAR (2021) (0)
- Equilibre de marche correspondant a la realite (2006) (0)
- Efficient distributed approximation algorithms via probabilistic tree embeddings (2012) (0)
- Ôôöóüüññøø Ðð××׬ Blockin Blockinøøóò Úúú Öøøñóúö Ññøöö Blockin× (2007) (0)
- Genomics of rare genetic diseases—experiences from India (2019) (0)
- 1 Description of the Stash Shuffle Algorithm 1 The Stash Shuffle algorithm (2018) (0)
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