Kannan Ramchandran

ORCID

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 194

Top Venues

CoRR

ISIT

IEEE Trans. Inf. Theory

Allerton

Publications

Nived Rajaraman, Marco Bondaschi, Kannan Ramchandran, Michael Gastpar, Ashok Vardhan Makkuva
Transformers on Markov Data: Constant Depth Suffices. CoRR (2024)
Justin Singh Kang, Ramtin Pedarsani, Kannan Ramchandran
The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning. Trans. Mach. Learn. Res. 2024 (2024)
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran, Tara Javidi, Arya Mazumdar
Competing Bandits in Non-Stationary Matching Markets. IEEE Trans. Inf. Theory 70 (4) (2024)
Nived Rajaraman, Jiantao Jiao, Kannan Ramchandran
Toward a Theory of Tokenization in LLMs. CoRR (2024)
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran
Model Selection for Generic Contextual Bandits. IEEE Trans. Inf. Theory 70 (1) (2024)
Justin Singh Kang, Yigit Efe Erginbas, Landon Butler, Ramtin Pedarsani, Kannan Ramchandran
Learning to Understand: Identifying Interactions via the Mobius Transform. CoRR (2024)
Yigit Efe Erginbas, Thomas A. Courtade, Kannan Ramchandran, Soham Phade
Online Pricing for Multi-User Multi-Item Markets. NeurIPS (2023)
Nived Rajaraman, Devvrit, Aryan Mokhtari, Kannan Ramchandran
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing. NeurIPS (2023)
Ajil Jalal, Justin Singh Kang, Ananya Uppal, Kannan Ramchandran, Eric Price
Learning a 1-layer conditional generative model in total variation. NeurIPS (2023)
Yigit Efe Erginbas, Justin Singh Kang, Amirali Aghazadeh, Kannan Ramchandran
Efficiently Computing Sparse Fourier Transforms of q-ary Functions. CoRR (2023)
Yaoqing Yang, Ryan Theisen, Liam Hodgkinson, Joseph E. Gonzalez, Kannan Ramchandran, Charles H. Martin, Michael W. Mahoney
Test Accuracy vs. Generalization Gap: Model Selection in NLP without Accessing Training or Testing Data. KDD (2023)
Vijay Kamble, Nihar B. Shah, David Marn, Abhay Parekh, Kannan Ramchandran
The Square Root Agreement Rule for Incentivizing Truthful Feedback on Online Platforms. Manag. Sci. 69 (1) (2023)
Yigit Efe Erginbas, Justin Singh Kang, Amirali Aghazadeh, Kannan Ramchandran
Efficiently Computing Sparse Fourier Transforms of q-ary Functions. ISIT (2023)
Nived Rajaraman, Yanjun Han, Jiantao Jiao, Kannan Ramchandran
Beyond UCB: Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits. CoRR (2023)
Yigit Efe Erginbas, Soham Phade, Kannan Ramchandran
Interactive Learning with Pricing for Optimal and Stable Allocations in Markets. AISTATS (2023)
Brett Levac, Ajil Jalal, Kannan Ramchandran, Jonathan I. Tamir
MRI Reconstruction with Side Information using Diffusion Models. ACSSC (2023)
Tianhao Wu, Banghua Zhu, Ruoyu Zhang, Zhaojin Wen, Kannan Ramchandran, Jiantao Jiao
Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment. CoRR (2023)
Orhan Öçal, Swanand Kadhe, Xiao Li, Kannan Ramchandran
Minimum-Rate Spectrum-Blind Sampling Based on Sparse-Graph Codes. IEEE Trans. Signal Process. 71 (2023)
Justin Singh Kang, Ramtin Pedarsani, Kannan Ramchandran
The Fair Value of Data Under Heterogeneous Privacy Constraints. CoRR (2023)
Nived Rajaraman, Devvrit, Aryan Mokhtari, Kannan Ramchandran
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing and Neural Networks with Quadratic Activations. CoRR (2023)
Amirali Aghazadeh, Nived Rajaraman, Tony Tu, Kannan Ramchandran
Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces. Trans. Mach. Learn. Res. 2023 (2023)
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran
Multi-agent Heterogeneous Stochastic Linear Bandits. ECML/PKDD (4) (2022)
Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael W. Mahoney, Joseph E. Gonzalez, Kannan Ramchandran, Prateek Mittal
Neurotoxin: Durable Backdoors in Federated Learning. CoRR (2022)
Kangwook Lee, Nihar B. Shah, Longbo Huang, Kannan Ramchandran
Addendum and Erratum to "The MDS Queue: Analysing the Latency Performance of Erasure Codes". IEEE Trans. Inf. Theory 68 (9) (2022)
Amirali Aghazadeh, Nived Rajaraman, Tony Tu, Kannan Ramchandran
Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces. CoRR (2022)
Yigit Efe Erginbas, Soham R. Phade, Kannan Ramchandran
Interactive Learning with Pricing for Optimal and Stable Allocations in Markets. CoRR (2022)
Yigit Efe Erginbas, Soham R. Phade, Kannan Ramchandran
Interactive Recommendations for Optimal Allocations in Markets with Constraints. CoRR (2022)
Avishek Ghosh, Ashwin Pananjady, Adityanand Guntuboyina, Kannan Ramchandran
Max-Affine Regression: Parameter Estimation for Gaussian Designs. IEEE Trans. Inf. Theory 68 (3) (2022)
Avishek Ghosh, Jichan Chung, Dong Yin, Kannan Ramchandran
An Efficient Framework for Clustered Federated Learning. IEEE Trans. Inf. Theory 68 (12) (2022)
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran, Tara Javidi, Arya Mazumdar
Decentralized Competing Bandits in Non-Stationary Matching Markets. CoRR (2022)
Yaoqing Yang, Ryan Theisen, Liam Hodgkinson, Joseph E. Gonzalez, Kannan Ramchandran, Charles H. Martin, Michael W. Mahoney
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data. CoRR (2022)
Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu, Jiantao Jiao, Kannan Ramchandran
Minimax Optimal Online Imitation Learning via Replay Estimation. NeurIPS (2022)
Zhengming Zhang, Ashwinee Panda, Linyue Song, Yaoqing Yang, Michael W. Mahoney, Prateek Mittal, Kannan Ramchandran, Joseph Gonzalez
Neurotoxin: Durable Backdoors in Federated Learning. ICML (2022)
Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu, Jiantao Jiao, Kannan Ramchandran
Minimax Optimal Online Imitation Learning via Replay Estimation. CoRR (2022)
Yaoqing Yang, Liam Hodgkinson, Ryan Theisen, Joe Zou, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney
Taxonomizing local versus global structure in neural network loss landscapes. CoRR (2021)
Nived Rajaraman, Yanjun Han, Lin F. Yang, Kannan Ramchandran, Jiantao Jiao
Provably Breaking the Quadratic Error Compounding Barrier in Imitation Learning, Optimally. CoRR (2021)
Yaoqing Yang, Liam Hodgkinson, Ryan Theisen, Joe Zou, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney
Taxonomizing local versus global structure in neural network loss landscapes. NeurIPS (2021)
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran
Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits. AISTATS (2021)
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran
Model Selection for Generic Contextual Bandits. CoRR (2021)
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran
Collaborative Learning and Personalization in Multi-Agent Stochastic Linear Bandits. CoRR (2021)
Swanand Kadhe, Nived Rajaraman, Kannan Ramchandran
FastShare: Scalable Secret Sharing by Leveraging Locality. ISIT (2021)
Avishek Ghosh, Sayak Ray Chowdhury, Kannan Ramchandran
Model Selection with Near Optimal Rates for Reinforcement Learning with General Model Classes. CoRR (2021)
Zhengming Zhang, Yaoqing Yang, Zhewei Yao, Yujun Yan, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney
Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models. IEEE BigData (2021)
Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney
Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism. KDD (2021)
Vipul Gupta, Avishek Ghosh, Michal Derezinski, Rajiv Khanna, Kannan Ramchandran, Michael W. Mahoney
LocalNewton: Reducing Communication Bottleneck for Distributed Learning. CoRR (2021)
Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar, Kannan Ramchandran
Escaping Saddle Points in Distributed Newton's Method with Communication efficiency and Byzantine Resilience. CoRR (2021)
Zihan Liu, Kannan Ramchandran
Adaptive Douglas-Rachford Splitting Algorithm from a Yosida Approximation Standpoint. SIAM J. Optim. 31 (3) (2021)
Vipul Gupta, Avishek Ghosh, Michal Derezinski, Rajiv Khanna, Kannan Ramchandran, Michael W. Mahoney
LocalNewton: Reducing communication rounds for distributed learning. UAI (2021)
Amirali Aghazadeh, Vipul Gupta, Alex DeWeese, Onur Ozan Koyluoglu, Kannan Ramchandran
BEAR: Sketching BFGS Algorithm for Ultra-High Dimensional Feature Selection in Sublinear Memory. MSML (2021)
Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran
On the Value of Interaction and Function Approximation in Imitation Learning. NeurIPS (2021)
Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar, Kannan Ramchandran
Communication-Efficient and Byzantine-Robust Distributed Learning With Error Feedback. IEEE J. Sel. Areas Inf. Theory 2 (3) (2021)
Swanand Kadhe, Nived Rajaraman, Onur Ozan Koyluoglu, Kannan Ramchandran
FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning. CoRR (2020)
Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney
Boundary thickness and robustness in learning models. CoRR (2020)
Amirali Aghazadeh, Vipul Gupta, Alex DeWeese, Onur Ozan Koyluoglu, Kannan Ramchandran
BEAR: Sketching BFGS Algorithm for Ultra-High Dimensional Feature Selection in Sublinear Memory. CoRR (2020)
Haewon Jeong, Yaoqing Yang, Vipul Gupta, Christian Engelmann, Tze Meng Low, Viveck R. Cadambe, Kannan Ramchandran, Pulkit Grover
3D Coded SUMMA: Communication-Efficient and Robust Parallel Matrix Multiplication. Euro-Par (2020)
Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar, Kannan Ramchandran
Communication-Efficient and Byzantine-Robust Distributed Learning. ITA (2020)
Avishek Ghosh, Kannan Ramchandran
Alternating Minimization Converges Super-Linearly for Mixed Linear Regression. CoRR (2020)
Avishek Ghosh, Jichan Chung, Dong Yin, Kannan Ramchandran
An Efficient Framework for Clustered Federated Learning. NeurIPS (2020)
Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar, Kannan Ramchandran
Communication Efficient and Byzantine Tolerant Distributed Learning. ISIT (2020)
Roel Dobbe, Ye Pu, Jingge Zhu, Kannan Ramchandran, Claire J. Tomlin
Local Differential Privacy for Multi-Agent Distributed Optimal Power Flow. ISGT-Europe (2020)
Swanand Kadhe, Onur Ozan Koyluoglu, Kannan Ramchandran
Communication-Efficient Gradient Coding for Straggler Mitigation in Distributed Learning. CoRR (2020)
Amirali Aghazadeh, Orhan Ocal, Kannan Ramchandran
CRISPRL and: Interpretable large-scale inference of DNA repair landscape based on a spectral approach. Bioinform. 36 (Supplement-1) (2020)
Kangwook Lee, Changho Suh, Kannan Ramchandran
Reprogramming GANs via Input Noise Design. ECML/PKDD (2) (2020)
Vipul Gupta, Dominic Carrano, Yaoqing Yang, Vaishaal Shankar, Thomas A. Courtade, Kannan Ramchandran
Serverless Straggler Mitigation using Local Error-Correcting Codes. CoRR (2020)
Avishek Ghosh, Jichan Chung, Dong Yin, Kannan Ramchandran
An Efficient Framework for Clustered Federated Learning. CoRR (2020)
Steven Cao, Swanand Kadhe, Kannan Ramchandran
CoVer: Collaborative Light-Node-Only Verification and Data Availability for Blockchains. Blockchain (2020)
Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran
Toward the Fundamental Limits of Imitation Learning. NeurIPS (2020)
Swanand Kadhe, Onur Ozan Koyluoglu, Kannan Ramchandran
Communication-Efficient Gradient Coding for Straggler Mitigation in Distributed Learning. ISIT (2020)
Steven Cao, Swanand Kadhe, Kannan Ramchandran
CoVer: Collaborative Light-Node-Only Verification and Data Availability for Blockchains. CoRR (2020)
Yaoqing Yang, Jichan Chung, Guanhua Wang, Vipul Gupta, Adarsh Karnati, Kenan Jiang, Ion Stoica, Joseph Gonzalez, Kannan Ramchandran
Robust Class Parallelism - Error Resilient Parallel Inference with Low Communication Cost. ACSSC (2020)
Vipul Gupta, Swanand Kadhe, Thomas A. Courtade, Michael W. Mahoney, Kannan Ramchandran
OverSketched Newton: Fast Convex Optimization for Serverless Systems. IEEE BigData (2020)
Avishek Ghosh, Kannan Ramchandran
Alternating Minimization Converges Super-Linearly for Mixed Linear Regression. AISTATS (2020)
Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran
Toward the Fundamental Limits of Imitation Learning. CoRR (2020)
Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar, Kannan Ramchandran
Communication Efficient Distributed Approximate Newton Method. ISIT (2020)
Vipul Gupta, Soham R. Phade, Thomas A. Courtade, Kannan Ramchandran
Utility-based Resource Allocation and Pricing for Serverless Computing. CoRR (2020)
Orhan Ocal, Kannan Ramchandran
Fast Compressive Large-Scale Matrix-Matrix Multiplication Using Product Codes. ISIT (2020)
Vipul Gupta, Dominic Carrano, Yaoqing Yang, Vaishaal Shankar, Thomas A. Courtade, Kannan Ramchandran
Serverless Straggler Mitigation using Error-Correcting Codes. ICDCS (2020)
Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney
Boundary thickness and robustness in learning models. NeurIPS (2020)
Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran
Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits. CoRR (2020)
Avishek Ghosh, Kannan Ramchandran
Some Performance Guarantees of Global LASSO with Local Assumptions for Convolutional Sparse Design Matrices. ISIT (2020)
Avishek Ghosh, Ashwin Pananjady, Aditya Guntuboyina, Kannan Ramchandran
Max-affine regression with universal parameter estimation for small-ball designs. ISIT (2020)
Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney
Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism. CoRR (2020)
Vipul Gupta, Swanand Kadhe, Thomas A. Courtade, Michael W. Mahoney, Kannan Ramchandran
OverSketched Newton: Fast Convex Optimization for Serverless Systems. CoRR (2019)
Xiao Li, Dong Yin, Sameer Pawar, Ramtin Pedarsani, Kannan Ramchandran
Sub-Linear Time Support Recovery for Compressed Sensing Using Sparse-Graph Codes. IEEE Trans. Inf. Theory 65 (10) (2019)
Swanand Kadhe, Jichan Chung, Kannan Ramchandran
SeF: A Secure Fountain Architecture for Slashing Storage Costs in Blockchains. CoRR (2019)
Swanand Kadhe, Onur Ozan Koyluoglu, Kannan Ramchandran
Gradient Coding Based on Block Designs for Mitigating Adversarial Stragglers. ISIT (2019)
Kangwook Lee, Kabir Chandrasekher, Ramtin Pedarsani, Kannan Ramchandran
SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing Based on Sparse-Graph Codes. IEEE Trans. Signal Process. 67 (17) (2019)
Kamil Nar, Orhan Ocal, S. Shankar Sastry, Kannan Ramchandran
Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples. CoRR (2019)
Avishek Ghosh, Ashwin Pananjady, Adityanand Guntuboyina, Kannan Ramchandran
Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation. CoRR (2019)
Orhan Ocal, Oguz H. Elibol, Gokce Keskin, Cory Stephenson, Anil Thomas, Kannan Ramchandran
Adversarially Trained Autoencoders for Parallel-data-free Voice Conversion. ICASSP (2019)
Avishek Ghosh, Justin Hong, Dong Yin, Kannan Ramchandran
Robust Federated Learning in a Heterogeneous Environment. CoRR (2019)
Orhan Ocal, Swanand Kadhe, Kannan Ramchandran
Low-degree Pseudo-Boolean Function Recovery Using Codes. ISIT (2019)
Kangwook Lee, Hoon Kim, Kyungmin Lee, Changho Suh, Kannan Ramchandran
Synthesizing Differentially Private Datasets using Random Mixing. ISIT (2019)
Angie Wang, Woo-Rham Bae, Jaeduk Han, Stevo Bailey, Orhan Ocal, Paul Rigge, Zhongkai Wang, Kannan Ramchandran, Elad Alon, Borivoje Nikolic
A Real-Time, 1.89-GHz Bandwidth, 175-kHz Resolution Sparse Spectral Analysis RISC-V SoC in 16-nm FinFET. IEEE J. Solid State Circuits 54 (7) (2019)
Sinho Chewi, Forest Yang, Avishek Ghosh, Abhay Parekh, Kannan Ramchandran
Matching Observations to Distributions: Efficient Estimation via Sparsified Hungarian Algorithm. Allerton (2019)
Swanand Kadhe, Onur Ozan Koyluoglu, Kannan Ramchandran
Gradient Coding Based on Block Designs for Mitigating Adversarial Stragglers. CoRR (2019)
Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar, Kannan Ramchandran
Communication-Efficient and Byzantine-Robust Distributed Learning. CoRR (2019)
Dong Yin, Kannan Ramchandran, Peter L. Bartlett
Rademacher Complexity for Adversarially Robust Generalization. ICML (2019)
Dong Yin, Yudong Chen, Kannan Ramchandran, Peter L. Bartlett
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning. ICML (2019)
Orhan Ocal, Oguz H. Elibol, Gokce Keskin, Cory Stephenson, Anil Thomas, Kannan Ramchandran
Adversarially Trained Autoencoders for Parallel-Data-Free Voice Conversion. CoRR (2019)

Kannan Ramchandran.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Kannan Ramchandran