A Note on SpanP Functions. - Meena Mahajan; Thomas Thierauf; N. V. Vinodchandran (Inf. Process. Lett., 1994)

A Note on Mod and Generalised Mod Classes. - Meena Mahajan; N. V. Vinodchandran (Inf. Process. Lett., 1995)

The Complexity of Exactly Learning Algebraic Concepts. (Extended Abstract). - Vikraman Arvind; N. V. Vinodchandran (ALT, 1996)

Exact Learning via Teaching Assistants (Extended Abstract). - Vikraman Arvind; N. V. Vinodchandran (ALT, 1997)

Improved Lowness Results for Solvable Black-box Group Problems. - N. V. Vinodchandran (FSTTCS, 1997)

Solvable Black-Box Group Problems are Low for PP. - Vikraman Arvind; N. V. Vinodchandran (Theor. Comput. Sci., 1997)

Super-Polynomial Versus Half-Exponential Circuit Size in the Exponential Hierarchy. - Peter Bro Miltersen; N. V. Vinodchandran; Osamu Watanabe 001 (COCOON, 1999)

Exact learning via teaching assistants. - Vikraman Arvind; N. V. Vinodchandran (Theor. Comput. Sci., 2000)

The counting complexity of group-definable languages. - Vikraman Arvind; N. V. Vinodchandran (Theor. Comput. Sci., 2000)

The Query Complexity of Program Checking by Constant-Depth Circuits. - Vikraman Arvind; K. V. Subrahmanyam 001; N. V. Vinodchandran (Chic. J. Theor. Comput. Sci., 2002)

Using Depth to Capture Average-Case Complexity. - Luis Antunes 002; Lance Fortnow; N. V. Vinodchandran (FCT, 2003)

Partial Bi-immunity and NP-Completeness. - John M. Hitchcock; Aduri Pavan; N. V. Vinodchandran (CCC, 2004)

Learning DNFs and Circuits Using Teaching Assistants. - N. V. Vinodchandran (COCOON, 2004)

SVM-based generalized multiple-instance learning via approximate box counting. - Qingping Tao; Stephen Donald Scott; N. V. Vinodchandran; Thomas Takeo Osugi (ICML, 2004)

An Extended Kernel for Generalized Multiple-Instance Learning. - Qingping Tao; Stephen Scott 001; N. V. Vinodchandran; Thomas Takeo Osugi; Brandon Mueller (ICTAI, 2004)

Polylogarithmic Round Arthur-Merlin Games and Random-Self-Reducibility - Aduri Pavan; N. V. Vinodchandran (Electron. Colloquium Comput. Complex., 2004)

AMexp[nsube](NP[cap]coNP)/poly. - N. V. Vinodchandran (Inf. Process. Lett., 2004)

Counting Complexity of Solvable Black-Box Group Problems. - N. V. Vinodchandran (SIAM J. Comput., 2004)

On computing disjoint paths with dependent cost structure in optical networks. - Ajay Kumar Todimala; Byrav Ramamurthy; N. V. Vinodchandran (BROADNETS, 2005)

CRTDH: an efficient key agreement scheme for secure group communications in wireless ad hoc networks. - Ravi K. Balachandran; Byrav Ramamurthy; Xukai Zou; N. Variyam Vinodchandran (ICC, 2005)

A balanced key tree approach for dynamic secure group communication. - Geng Hao; N. V. Vinodchandran; Byrav Ramamurthy; Xukai Zou (ICCCN, 2005)

Derandomizing Arthur-Merlin Games using Hitting Sets. - Peter Bro Miltersen; N. V. Vinodchandran (Comput. Complex., 2005)

Extracting Kolmogorov Complexity with Applications to Dimension Zero-One Laws - Lance Fortnow; John M. Hitchcock; Aduri Pavan; N. V. Vinodchandran; Fengming Wang (Electron. Colloquium Comput. Complex., 2005)

Nondeterministic circuit minimization problem and derandomizing Arthur-Merlin games. - N. Variyam Vinodchandran (Int. J. Found. Comput. Sci., 2005)

Entropy rates and finite-state dimension. - Chris Bourke; John M. Hitchcock; N. V. Vinodchandran (Theor. Comput. Sci., 2005)

A note on the circuit complexity of PP. - N. V. Vinodchandran (Theor. Comput. Sci., 2005)

Some Results on Average-Case Hardness Within the Polynomial Hierarchy. - Aduri Pavan; Rahul Santhanam; N. V. Vinodchandran (FSTTCS, 2006)

A New Cryptographic Scheme for Securing Dynamic Conferences in Data Networks. - Sarang Deshpande; Ajay Kumar Todimala; Ravi K. Balachandran; Byrav Ramamurthy; Xukai Zou; N. V. Vinodchandran (ICC, 2006)

Dimension, entropy rates, and compression. - John M. Hitchcock; N. V. Vinodchandran (J. Comput. Syst. Sci., 2006)

Computational depth: Concept and applications. - Luis Antunes 002; Lance Fortnow; Dieter van Melkebeek; N. V. Vinodchandran (Theor. Comput. Sci., 2006)

Polylogarithmic-round interactive proofs for coNP collapse the exponential hierarchy. - Aduri Pavan; Alan L. Selman; Samik Sengupta; N. V. Vinodchandran (Theor. Comput. Sci., 2007)

2-Local Random Reductions to 3-Valued Functions. - Aduri Pavan; N. V. Vinodchandran (Comput. Complex., 2008)

On reoptimizing multi-class classifiers. - Chris Bourke; Kun Deng; Stephen D. Scott 001; Robert E. Schapire; N. V. Vinodchandran (Mach. Learn., 2008)

Partial Bi-immunity, Scaled Dimension, and NP-Completeness. - John M. Hitchcock; Aduri Pavan; N. V. Vinodchandran (Theory Comput. Syst., 2008)

Relations between Average-Case and Worst-Case Complexity. - Aduri Pavan; N. V. Vinodchandran (Theory Comput. Syst., 2008)

Kernels for Generalized Multiple-Instance Learning. - Qingping Tao; Stephen D. Scott 001; N. V. Vinodchandran; Thomas Takeo Osugi; Brandon Mueller (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

An efficient and attack-resistant key agreement scheme for secure group communications in mobile ad-hoc networks. - Ravi K. Balachandran; Xukai Zou; Byrav Ramamurthy; Amandeep Thukral; N. Variyam Vinodchandran (Wirel. Commun. Mob. Comput., 2008)

Kolmogorov Complexity in Randomness Extraction. - John M. Hitchcock; Aduri Pavan; N. V. Vinodchandran (Electron. Colloquium Comput. Complex., 2009)

A log-space algorithm for reachability in planar DAGs with few sources. - Derrick Stolee; Chris Bourke; N. V. Vinodchandran (Electron. Colloquium Comput. Complex., 2009)

Directed Planar Reachability Is in Unambiguous Log-Space. - Chris Bourke; Raghunath Tewari; N. V. Vinodchandran (ACM Trans. Comput. Theory, 2009)

A Log-Space Algorithm for Reachability in Planar Acyclic Digraphs with Few Sources. - Derrick Stolee; Chris Bourke; N. V. Vinodchandran (CCC, 2010)

Resource-bounded Dimension in Computational Learning Theory - Ricard Gavaldà; María López-Valdés; Elvira Mayordomo; N. V. Vinodchandran (CoRR, 2010)

On the Power of Unambiguity in Logspace. - Aduri Pavan; Raghunath Tewari; N. V. Vinodchandran (Electron. Colloquium Comput. Complex., 2010)

Space-Efficient Algorithms for Reachability in Surface-Embedded Graphs. - Derrick Stolee; N. V. Vinodchandran (Electron. Colloquium Comput. Complex., 2010)

Green's Theorem and Isolation in Planar Graphs. - Raghunath Tewari; N. V. Vinodchandran (Electron. Colloquium Comput. Complex., 2010)

On the power of unambiguity in log-space. - Aduri Pavan; Raghunath Tewari; N. V. Vinodchandran (Comput. Complex., 2012)

Space complexity of perfect matching in bounded genus bipartite graphs. - Samir Datta; Raghav Kulkarni; Raghunath Tewari; N. V. Vinodchandran (J. Comput. Syst. Sci., 2012)

An O(n½+∑)-Space and Polynomial-Time Algorithm for Directed Planar Reachability. - Tatsuya Imai; Kotaro Nakagawa; Aduri Pavan; N. V. Vinodchandran; Osamu Watanabe 001 (CCC, 2013)

ReachFewL = ReachUL. - Brady Garvin; Derrick Stolee; Raghunath Tewari; N. V. Vinodchandran (Comput. Complex., 2014)

New Time-Space Upperbounds for Directed Reachability in High-genus and H-minor-free Graphs. - Diptarka Chakraborty; Aduri Pavan; Raghunath Tewari; N. Variyam Vinodchandran; Lin F. Yang (Electron. Colloquium Comput. Complex., 2014)

Space Complexity of the Directed Reachability Problem over Surface-Embedded Graphs. - N. Variyam Vinodchandran (Electron. Colloquium Comput. Complex., 2014)

On Probabilistic Space-Bounded Machines with Multiple Access to Random Tape. - Debasis Mandal; Aduri Pavan; N. V. Vinodchandran (MFCS (2), 2015)

On Optimal Language Compression for Sets in PSPACE/poly. - N. V. Vinodchandran; Marius Zimand (Theory Comput. Syst., 2015)

Computing triangle and open-wedge heavy-hitters in large networks. - Aduri Pavan; Paul Quint; Stephen D. Scott 001; N. V. Vinodchandran; J. Smith (IEEE BigData, 2016)

Algorithms for k-median Clustering over Distributed Streams. - Sutanu Gayen; N. V. Vinodchandran (COCOON, 2016)

A Note on the Advice Complexity of Multipass Randomized Logspace. - Peter Dixon 002; Debasis Mandal; Aduri Pavan; N. V. Vinodchandran (MFCS, 2016)

Constrained Group Testing to Predict Binding Response of Candidate Compounds. - Paul Quint; Stephen D. Scott 001; N. V. Vinodchandran; Bradley Worley (SDM, 2016)

Budgeted testing through an algorithmic lens. - Myra B. Cohen; Aduri Pavan; N. V. Vinodchandran (SIGSOFT FSE, 2016)

Fractal features for automatic detection of dysarthria. - Taylor Spangler; N. V. Vinodchandran; Ashok Samal; Jordan R. Green (BHI, 2017)

KmerEstimate: A Streaming Algorithm for Estimating k-mer Counts with Optimal Space Usage. - Sairam Behera; Sutanu Gayen; Jitender S. Deogun; N. V. Vinodchandran (BCB, 2018)

On Pseudodeterministic Approximation Algorithms. - Peter Dixon 002; Aduri Pavan; N. V. Vinodchandran (MFCS, 2018)

New Algorithms for Distributed Sliding Windows. - Sutanu Gayen; N. V. Vinodchandran (SWAT, 2018)

New Bounds for the CLIQUE-GAP Problem Using Graph Decomposition Theory. - Vladimir Braverman; Zaoxing Liu; Tejasvam Singh; N. V. Vinodchandran; Lin F. Yang (Algorithmica, 2018)

A Sublinear-space and Polynomial-time Separator Algorithm for Planar Graphs. - Ryo Ashida; Tatsuya Imai; Kotaro Nakagawa; A. Pavan 001; N. V. Vinodchandran; Osamu Watanabe 001 (Electron. Colloquium Comput. Complex., 2019)

Learning and Sampling of Atomic Interventions from Observations. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; Ashwin Maran; N. Variyam Vinodchandran (ICML, 2020)

Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning. - Arnab Bhattacharyya 001; Sutanu Gayen; Kuldeep S. Meel; N. V. Vinodchandran (NeurIPS, 2020)

Efficiently Learning and Sampling Interventional Distributions from Observations. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; Ashwin Maran; N. V. Vinodchandran (CoRR, 2020)

Perfect Zero Knowledge: New Upperbounds and Relativized Separations. - Peter Dixon 002; Sutanu Gayen; A. Pavan 001; N. V. Vinodchandran (IACR Cryptol. ePrint Arch., 2020)

Testing Product Distributions: A Closer Look. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; N. V. Vinodchandran (ALT, 2021)

Complete Problems for Multi-Pseudodeterministic Computations. - Peter Dixon 002; A. Pavan 001; N. V. Vinodchandran (ITCS, 2021)

Estimating the Size of Union of Sets in Streaming Models. - Kuldeep S. Meel; N. V. Vinodchandran; Sourav Chakraborty 001 (PODS, 2021)

Model Counting meets F0 Estimation. - Aduri Pavan; N. V. Vinodchandran; Arnab Bhattacharyya 001; Kuldeep S. Meel (PODS, 2021)

Near-optimal learning of tree-structured distributions by Chow-Liu. - Arnab Bhattacharyya 001; Sutanu Gayen; Eric Price 001; N. V. Vinodchandran (STOC, 2021)

Model Counting meets F0 Estimation. - Aduri Pavan; N. V. Vinodchandran; Arnab Bhattacharyya 001; Kuldeep S. Meel (CoRR, 2021)

Efficient inference of interventional distributions. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; Vedant Raval; N. V. Vinodchandran (CoRR, 2021)

Promise Problems Meet Pseudodeterminism. - Peter Dixon 002; Aduri Pavan; N. V. Vinodchandran (Electron. Colloquium Comput. Complex., 2021)

Efficient interventional distribution learning in the PAC framework. - Arnab Bhattacharyya 001; Sutanu Gayen; Saravanan Kandasamy 002; Vedant Raval; N. Variyam Vinodchandran (AISTATS, 2022)

Distinct Elements in Streams: An Algorithm for the (Text) Book. - Sourav Chakraborty 001; N. V. Vinodchandran; Kuldeep S. Meel (ESA, 2022)

A Scalable t-wise Coverage Estimator. - Eduard Baranov; Sourav Chakraborty 001; Axel Legay; Kuldeep S. Meel; N. Variyam Vinodchandran (ICSE, 2022)

Estimation of the Size of Union of Delphic Sets: Achieving Independence from Stream Size. - Kuldeep S. Meel; Sourav Chakraborty 001; N. V. Vinodchandran (PODS, 2022)

Pseudodeterminism: promises and lowerbounds. - Peter Dixon 002; Aduri Pavan; Jason Vander Woude; N. V. Vinodchandran (STOC, 2022)

The Geometry of Rounding. - Jason Vander Woude; Peter Dixon 002; A. Pavan 001; Jamie Radcliffe; N. V. Vinodchandran (Electron. Colloquium Comput. Complex., 2022)

Model Counting Meets Distinct Elements in a Data Stream. - Aduri Pavan; N. V. Vinodchandran; Arnab Bhattacharyya 001; Kuldeep S. Meel (SIGMOD Rec., 2022)

Constraint Optimization over Semirings. - Aduri Pavan; Kuldeep S. Meel; N. V. Vinodchandran; Arnab Bhattacharyya 001 (AAAI, 2023)

On Approximating Total Variation Distance. - Arnab Bhattacharyya 001; Sutanu Gayen; Kuldeep S. Meel; Dimitrios Myrisiotis; A. Pavan 001; N. V. Vinodchandran (IJCAI, 2023)

List and Certificate Complexities in Replicable Learning. - Peter Dixon 002; Aduri Pavan; Jason Vander Woude; N. V. Vinodchandran (NeurIPS, 2023)

Brief Announcement: Relations Between Space-Bounded and Adaptive Massively Parallel Computations. - Michael Chen; A. Pavan 001; N. V. Vinodchandran (DISC, 2023)

Geometry of Rounding: Near Optimal Bounds and a New Neighborhood Sperner's Lemma. - Jason Vander Woude; Peter Dixon 002; Aduri Pavan; Jamie Radcliffe; N. V. Vinodchandran (CoRR, 2023)

Total Variation Distance Estimation Is as Easy as Probabilistic Inference. - Arnab Bhattacharyya 001; Sutanu Gayen; Kuldeep S. Meel; Dimitrios Myrisiotis; A. Pavan 001; N. V. Vinodchandran (Electron. Colloquium Comput. Complex., 2023)

Near-Optimal Learning of Tree-Structured Distributions by Chow and Liu. - Arnab Bhattacharyya 001; Sutanu Gayen; Eric Price 001; Vincent Y. F. Tan; N. V. Vinodchandran (SIAM J. Comput., 2023)

Model Counting Meets Distinct Elements. - A. Pavan 001; N. V. Vinodchandran; Arnab Bhattacharyya 001; Kuldeep S. Meel (Commun. ACM, 2023)

Model Counting Meets F0 Estimation. - A. Pavan 001; N. Variyam Vinodchandran; Arnab Bhattacharyya 001; Kuldeep S. Meel (ACM Trans. Database Syst., 2023)

Improved Streaming Algorithm for the Klee's Measure Problem and Generalizations. - Mridul Nandi; N. V. Vinodchandran; Arijit Ghosh; Kuldeep S. Meel; Soumit Pal; Sourav Chakraborty 001 (APPROX/RANDOM, 2024)

Total Variation Distance Meets Probabilistic Inference. - Arnab Bhattacharyya 001; Sutanu Gayen; Kuldeep S. Meel; Dimitrios Myrisiotis; A. Pavan 001; N. V. Vinodchandran (ICML, 2024)

Replicability in Learning: Geometric Partitions and KKM-Sperner Lemma. - Jason Vander Woude; Peter Dixon 002; Aduri Pavan; Jamie Radcliffe; N. V. Vinodchandran (NeurIPS, 2024)

Distribution Learning Meets Graph Structure Sampling. - Arnab Bhattacharyya 001; Sutanu Gayen; Philips George John; Sayantan Sen; N. V. Vinodchandran (CoRR, 2024)

Point Prediction for Streaming Data. - Aleena Chanda; N. V. Vinodchandran; Bertrand S. Clarke (CoRR, 2024)

On the Feasibility of Forgetting in Data Streams. - Aduri Pavan; Sourav Chakraborty 001; N. V. Vinodchandran; Kuldeep S. Meel (Proc. ACM Manag. Data, 2024)

A Scalable $t$t-Wise Coverage Estimator: Algorithms and Applications. - Eduard Baranov; Sourav Chakraborty 001; Axel Legay; Kuldeep S. Meel; N. Variyam Vinodchandran (IEEE Trans. Software Eng., 2024)

Computational Explorations of Total Variation Distance. - Arnab Bhattacharyya 001; Sutanu Gayen; Kuldeep S. Meel; Dimitrios Myrisiotis; Aduri Pavan; N. V. Vinodchandran (ICLR, 2025)

Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds. - Michael Chen; Aduri Pavan; N. V. Vinodchandran; Ruosong Wang; Lin Yang 011 (ICLR, 2025)

Total variation distance for product distributions is #P-complete. - Arnab Bhattacharyya 001; Sutanu Gayen; Kuldeep S. Meel; Dimitrios Myrisiotis; A. Pavan 001; N. V. Vinodchandran (Inf. Process. Lett., 2025)