J: Journal. C: Conference. W: Workshop (peer reviewed)
On the Theory of Continual Learning with Gradient Descent for Neural Networks--Hossein Taheri, Avishek Ghosh and Arya Mazumdar, 2025
Incentivize Contribution and Learn Parameters Too: Federated Learning with Strategic Data Owners -- Drashthi Doshi, Aditya Vema Reddy Kesari, Swaprava Nath, Avishek Ghosh, Suhas S Kowshik, 2025
LocalKMeans: Convergence of Lloyd's Algorithm with Distributed Local Iterations-- Harsh Vardhan, Heng Zhu, Avishek Ghosh and Arya Mazumdar, 2025
Competing Bandits in Decentralized Large Contextual Matching Markets -- Satush Parikh, Soumya Basu, Avishek Ghosh, Abishek Sankararaman, 2024
Detection of sensor attacks in cyber-physical systems: algorithm and guarantees; Souvik Das, Avishek Ghosh and Debasish Chatterjee, 2024
[C] Expectation Maximization (EM) Converges for General Agnostic Mixtures-- Avishek Ghosh; IEEE International Symposium on Information Theory (ISIT) 2026, Guangzhou, China
[C] Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE -- Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh, Sunita Sarawagi -- [Invited for presentation at] International Conference on Learning Representations (ICLR), 2026, Rio de Janeiro, Brazil
[J] Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE -- Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh, Sunita Sarawagi --- Transactions in Machine Learning Research (TMLR), 2025.
[C] Near Optimal Best Arm Identification for Clustered Bandits -- Yash, Avishek Ghosh, Nikhil Karamchandani; International Conference on Machine Learning (ICML), 2025, Vancouver, Canada
[C] Learning and Generalization With Mixture Data; Harsh Vardhan, Avishek Ghosh and Arya Mazumdar-- IEEE International Symposium on Information Theory (ISIT) 2025, Ann Arbor (Michigan), USA
[C] Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms; Avishek Ghosh and Arya Mazumdar; International Conference on Machine Learning (ICML), 2024, Vienna, Austria
[C] PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect; Lokesh N, Pranava Singhal, Avishek Ghosh and Sunita Sarawagi; International Conference on Machine Learning (ICML), 2024, Vienna, Austria
[J] An Improved Algorithm for Clustered Federated Learning; Harshvardhan, Avishek Ghosh and Arya Mazumdar --- Transactions in Machine Learning Research (TMLR), 2024.
[C] Explore-then-Commit Algorithms for Decentralized Two-sided Matching Markets; Tejas Pagare, Avishek Ghosh-- IEEE International Symposium on Information Theory (ISIT) 2024, Athens, Greece
[C] DIST-CURE: A Robust Distributed Learning Algorithm with Cubic Regularized Newton; Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar-- IEEE International Symposium on Information Theory (ISIT) 2024, Athens, Greece
[C] Detection of False Data Injection Attacks in Cyber-Physical Systems; Souvik Das, Avishek Ghosh, Debasish Chatterjee-- IEEE International Symposium on Information Theory (ISIT) 2024, Athens, Greece
[W] Leveraging a Simulator for Learning Causal Representations for CATE from Post-Treatment Covariates-- Lokesh N, Pranava Singhal, Avishek Ghosh and Sunita Sarawagi, Causal Representation Learning Workshop, NeurIPS 2024
[J] Decentralized Competing Bandits In Non-Stationary Matching Markets; Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran, Tara Javidi and Arya Mazumdar-- IEEE Transactions on Information Theory, 2023.
[C] Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference; Debangshu Banerjee, Avishek Ghosh, Sayak Raychowdhury and Aditya Gopalan -- International Conference on Artificial Intelligence and Statistics (AISTATS) 2023, Valencia, Spain
[J] Model Selection for Generic Contextual Bandits; Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran -- IEEE Transactions on Information Theory, 2023.
[J] Understanding and Control of Zener Pinning via Phase Field and Ensemble Learning; Sukriti Manna, Henry Chan, Avishek Ghosh, Tamoghna Chakrabarti and Subramanian Sankaranarayanan -- Computational Materials Science, 2023
[C] Optimal Compression of Unit Norm Vectors in the High Distortion Regime; Heng Zhu, Avishek Ghosh, Arya Mazumdar, -- IEEE International Symposium on Information Theory (ISIT) 2023, Taipei, Taiwan
[W] Two-Sided Bandit Learning in Fully-Decentralized Matching Markets; Tejas Pagare and Avishek Ghosh -- International Conference on Machine Learning (ICML) Workshop on Many Facets of Preference-Based Learning, Hawaii, 2023
[W] Decentralized Competing Bandits In Non-Stationary Matching Markets; Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran, Tara Javidi and Arya Mazumdar -- International Conference on Machine Learning (ICML) Workshop on Many Facets of Preference-Based Learning, Hawaii, 2023
[W] An improved algorithm for Clustered Federated Learning; Harshvardhan, Avishek Ghosh and Arya Mazumdar -- International Conference on Machine Learning (ICML) Workshop on Federated Learning and Analytics, Hawaii, 2023
[W] Escaping Saddle Points in Distributed Newton's Method with Communication efficiency and Byzantine Resilience; Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar-- International Conference on Machine Learning (ICML) Workshop on Federated Learning and Analytics, Hawaii, 2023
[W] An improved algorithm for Clustered Federated Learning; Harshvardhan, Avishek Ghosh and Arya Mazumdar -- Information Theory and Applications (ITA), Student Poster, 2023, San Diego, USA.
[J] An Efficient Framework for Clustered Federated Learning (long version) -- Avishek Ghosh, Jichan Chung, Dong Yin, Kannan Ramchandran -- IEEE Transactions on Information Theory, 2022.
[J] Max-Affine Regression: Parameter Estimation for Gaussian Designs; Avishek Ghosh, Ashwin Pananjady, Aditya Guntuboyina, Kannan Ramchandran, IEEE Transactions on Information Theory, 2022.
[C] Breaking the $\sqrt{T}$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits; Avishek Ghosh and Abishek Sankararaman, International Conference on Machine Learning (ICML), 2022, Baltimore, USA
[C] On Learning Mixture of Linear Regressions in the Non-Realizable Setting; Avishek Ghosh, Arya Mazumdar, Soumyabrata Pal and Rajat Sen, International Conference on Machine Learning (ICML), 2022, Baltimore, USA
[C] Model Selection in Reinforcement Learning with General Function Approximations; Avishek Ghosh and Sayak Ray Chowdhury-- European Conference on Machine Learning (ECML-PKDD), 2022
[C] Multi-Agent Heterogeneous Stochastic Linear Bandits; Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran-- European Conference on Machine Learning (ECML-PKDD), 2022
[W] Distributed Newton Can Communicate Less and Resist Byzantine Workers -- Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar-- NSF-TRIPODS Workshop on Communication Efficient Distributed Optimization, 2022
[W] Escaping Saddle Points in Distributed Newton's Method with Communication efficiency and Byzantine Resilience; Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar, Kannan Ramchandran -- NSF-TRIPODS Workshop on Communication Efficient Distributed Optimization, 2022
[C] Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits -- Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran-- International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
[C] LocalNewton: Reducing Communication Rounds for Distributed Learning --- Vipul Gupta, Avishek Ghosh, Michal Derezinski, Rajiv Khanna, Kannan Ramchandran, Michael W Mahoney-- Uncertainty in Artificial Intelligence (UAI), 2021
[J] Communication-Efficient and Byzantine-Robust Distributed Learning with Error Feedback; Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar and Kannan Ramchandran, IEEE Journal on Selected Areas in Information Theory, 2021.
[C] An Efficient Framework for Clustered Federated Learning -- Avishek Ghosh, Jichan Chung, Dong Yin, Kannan Ramchandran -- Annual Conference on Neural Information Processing Systems (NeurIPS), 2020
[C] Distributed Newton Can Communicate Less and Resist Byzantine Workers -- Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar -- Annual Conference on Neural Information Processing Systems (NeurIPS), 2020.
[C] Alternating Minimization Converges Super-linearly for Mixed Linear Regression; Avishek Ghosh and Kannan Ramchandran -- International Conference on Artificial Intelligence and Statistics (AISTATS), 2020, Sicily, Italy.
[C] Max-affine Regression with Universal Parameter Estimation for Small-ball Designs; Avishek Ghosh, Ashwin Pananjady, Aditya Guntuboyina, Kannan Ramchandran -- IEEE International Symposium on Information Theory (ISIT), 2020, LA, USA.
[C] Communication Efficient Distributed Approximate Newton Method; Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar, Kannan Ramchandran -- IEEE International Symposium on Information Theory (ISIT), 2020, LA, USA.
[C] Communication Efficient and Byzantine Tolerant Distributed Learning; Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar, Kannan Ramchandran -- IEEE International Symposium on Information Theory (ISIT), 2020, LA, USA.
[C] Some Performance Guarantees of Global LASSO with Local Assumptions for Convolutional Sparse Design Matrices; Avishek Ghosh, Kannan Ramchandran -- IEEE International Symposium on Information Theory (ISIT), 2020, LA, USA.
[W] Model Selection for Finite and Continuous-Armed Stochastic Contextual Bandits-- Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran -- International Conference on Machine Learning (ICML) Workshop on Theoretical Foundations of Reinforcement Learning and Privacy, 2020, Austria.
[W] An Efficient Framework for Clustered Federated Learning -- Avishek Ghosh, Jichan Chung, Dong Yin, Kannan Ramchandran -- International Conference on Machine Learning (ICML) Workshop on Federated Learning and Privacy, 2020, Austria.
[W] Distributed Newton Can Communicate Less and Resist Byzantine Workers (short version) -- Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar -- International Conference on Machine Learning (ICML) Workshop on Beyond First Order Opt. in ML, 2020, Austria.
[W] Communication-Efficient Byzantine-Robust Distributed Learning-- Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar and Kannan Ramchandran-- Information Theory and Applications (ITA), 2020, San Diego, USA.
[C] Matching Observations to Distributions: Efficient Estimation via Sparsified Hungarian Algorithm; Sinho Chewi, Forest Yang, Avishek Ghosh, Abhay Parekh and Kannan Ramchandran -- Allerton Conference on Communication, Control, and Computing, 2019, IL, USA.
[W] Alternating Minimization for Max-Affine Regression-- Avishek Ghosh, Ashwin Pananjady, Aditya Guntuboyina, Kannan Ramchandran -- Signal Processing with Adaptive Sparse Structured Representations (SPARS), 2019 , Toulouse, France.
[W] Max affine regression: algorithm and analysis-- Avishek Ghosh, Ashwin Pananjady, Aditya Guntuboyina, Kannan Ramchandran, IND-STATS (Innovations in Data and Statistical Sciences), IIT Bombay, 2019, India
[W] Robust Heterogeneous Federated Learning-- Avishek Ghosh, Justin Hong, Dong Yin, Kannan Ramchandran -- International Conference on Machine Learning (ICML) Workshop on Privacy and Security in ML, 2019, LA, USA.
[C] Online Scoring with Delayed Information: A Convex Optimization Viewpoint ; Avishek Ghosh, Kannan Ramchandran -- Allerton Conference on Communication, Control, and Computing (2018) , IL, USA.
[C] Faster Data-access in Large-scale Systems: Network-scale Latency Analysis under General Service-time Distributions ; Avishek Ghosh, Kannan Ramchandran -- Allerton Conference on Communication, Control, and Computing (2018) , IL, USA.
[J] Asynchronous Stochastic Approximation Based Learning Algorithms for As-You-Go Deployment of Wireless Relay Networks along a Line; Arpan Chattopadhyay, Avishek Ghosh , Anurag Kumar. IEEE Transactions on Mobile Computing, 2018
[C] Misspecified Linear Bandits ; Avishek Ghosh, Sayak Ray Chowdhury and Aditya Gopalan -- AAAI Conference on Artificial Intelligence (AAAI), 2017, Sanfrancisco, USA.
[J] Measurement Based As-You-Go Deployment of Two-Connected Wireless Relay Networks; Avishek Ghosh, Arpan Chattopadhyay, Arora Anish, Anurag Kumar. ACM Transactions on Sensor Networks, 2017.
[C] As-you-go deployment of a 2-connected wireless relay network for sensor-sink interconnection; Avishek Ghosh, Arpan Chattopadhyay, Anish Arora, and Anurag Kumar; IEEE Signal Processing and Communications (IEEE-SPCOM), 2014, Bangalore, India.
[C] Impromptu Deployment of Wireless Relay Networks: Experiences Along a Forest Trail; Arpan Chattopadhyay, Avishek Ghosh, Akhila S Rao, Bharat Dwivedi, SVR Anand, Marceau Coupechoux, Anurag Kumar -- IEEE Mobile Ad Hoc and Sensor Systems (IEEE-MASS), 2014.
[J] A novel genetic algorithm to solve travelling salesman problem and blocking flow shop scheduling problem; A. Chowdhury, A. Ghosh, S. Sinha, S. Das and A Ghosh International Journal Bio-Inspired Computation (IJBIC) 2013.
[C] Linear phase low pass FIR filter design using Genetic Particle Swarm Optimization with dynamically varying neighbourhood technique ; Avishek Ghosh, Arnab Ghosh, Arkabandhu Chowdhury, Amit Konar, Eunjin Kim, Atulya K Nagar -- IEEE Congress on Evolutionary Computation (IEEE-CEC), 2012.
[C] Multi-robot cooperative box-pushing problem using multi-objective particle swarm optimization Technique ; Arnab Ghosh, Avishek Ghosh, A Konar, R Janarthanan -- World Congress on Information and Communication Technologies (WICT), 2012.
[C] An evolutionary approach to drug-design using quantam binary particle swarm optimization algorithm; Avishek Ghosh, Arnab Ghosh, Arkabandhu Chowdhury, Jubin Hazra -- IEEE Students' Conference on Electrical, Electronics and Computer Science, 2012.
[C] Application of Integral Value Transformation (IVT) in a Specialized Computer Network Design; Souvik Naskar, Avishek Ghosh, Pabitra Pal Choudhury -- 99th Indian Science Congress, 2012.
[J] Integral Value Transformations: A Class of Affine Discrete Dynamical Systems and an Application; Sk. S. Hassan, P. Pal Choudhury, B. K. Nayak, Avishek Ghosh, J. Banerjee, Journal of Advanced Research in Applied Mathematics (JARAM), 2011.
[C] Fractal String Generation and Its Application in Music Composition; Avishek Ghosh, Joydeep Banerjee, Sk. S. Hassan, P. Pal Choudhury. Published in the Proceedings of Mathematical and Statistical Modeling in Innovative Areas (MASTMIA, 2011).
Provable and Efficient Algorithms for Federated, Batch and Reinforcement Learning (see here) --- Avishek Ghosh--- Dept. of Electrical Engineering and Computer Sciences, UC Berkeley, May 2021
As-You-Go Deployment of 2 connected Wireless Sensor Networks; Decision Theoretic based design --- Avishek Ghosh--- Dept. of ECE, Indian Institute of Science (IISc) Bangalore, May 2014