Kunal Talwar

28.0k citations
93 papers · 7.8k indexed · 3 hit papers · h-index 30

Kunal Talwar

86 papers receiving 7.4k citations

Hit Papers

Deep Learning with Differential Privacy3.0k200720262013201950010001.5k2.0k2.5k

Peers

Kunal Talwar
Comparison fields: 5 of 132
  • Artificial Intelligence 5.1k
  • Computer Science Applications 787
  • Health Informatics 152
  • Computer Networks and Communications 1.9k
  • Information Systems 1.4k
Replace Xiaokui Xiao with:
Xiaokui Xiao Singapore
Hongwei Li China
Benjamin W. Wah United States
Frank McSherry United States
Toniann Pitassi Canada
Toby Walsh Australia
Ximeng Liu China
Aaron Roth United States
Douglas C. Schmidt United States
Alistair Moffat Australia
Kunal Talwar relative to Xiaokui Xiao Singapore Xiaokui Xiao's profile →
Citations per field
00.5×3.7×
Xiaokui Xiao · 1×
Citations per year

Countries citing papers authored by Kunal Talwar

Since Specialization
Citations

This map shows the geographic impact of Kunal Talwar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kunal Talwar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kunal Talwar more than expected).

Fields of papers citing papers by Kunal Talwar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kunal Talwar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kunal Talwar. The network helps show where Kunal Talwar may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Kunal Talwar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kunal Talwar Line = papers co-authored together Kunal Talwar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry
20213
2
Lossless Compression of Efficient Private Local Randomizers
20212
3
Characterizing Structural Regularities of Labeled Data in Overparameterized Models
20217
4
Exploring the Memorization-Generalization Continuum in Deep Learning
20202
5
Private Stochastic Convex Optimization with Optimal Rates
201910
6
Adversarially Robust Generalization Requires More Data
201856
7
Short and Deep: Sketching and Neural Networks
20172
8
Nearly-optimal private LASSO
201535
9
Analyze Gauss: optimal bounds for privacy-preserving PCA
20141
10 20143
11 201182
12
The Limits of Two-Party Differential Privacy.
201118
13 20107
14
Hard Instances for Satisfiability and Quasi-one-way Functions
20102
15 200937
16
Hardness of Low Congestion Routing in Directed Graphs
20066
17 200621
18 200375
19 200331
20
Detecting format string vulnerabilities with type qualifiers
2001257

About Kunal Talwar

Kunal Talwar is a scholar working on Computational Theory and Mathematics, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 93 papers that have together received 7.8k indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (36 papers), Privacy-Preserving Technologies in Data (28 papers), Advanced Graph Theory Research (19 papers), Cryptography and Data Security (17 papers), Optimization and Search Problems (16 papers), Stochastic Gradient Optimization Techniques (10 papers), Machine Learning and Algorithms (9 papers) and Auction Theory and Applications (9 papers). The work is most often cited by research in Artificial Intelligence (5.1k citations), Computer Science Applications (787 citations) and Health Informatics (152 citations). Kunal Talwar has collaborated with scholars based in United States, United Kingdom and Israel. Frequent co-authors include Frank McSherry, Li Zhang, Martı́n Abadi, Ian Goodfellow, Ilya Mironov, H. Brendan McMahan, Andy Chu, Satish Rao, Udi Wieder and Jittat Fakcharoenphol. Their work appears in journals such as Algorithmica, Theoretical Computer Science, SIAM Journal on Computing, Random Structures and Algorithms and Journal of Computer and System Sciences.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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