| 2026 | ISIT | Expectation Maximization (EM) Converges for General Agnostic Mixtures. | Avishek Ghosh |
| 2025 | ICML | Near Optimal Best Arm Identification for Clustered Bandits. | Yash, Avishek Ghosh, Nikhil Karamchandani |
| 2025 | ISIT | Learning and Generalization with Mixture Data. | Harsh Vardhan, Avishek Ghosh, Arya Mazumdar |
| 2024 | ICML | Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms. | Avishek Ghosh, Arya Mazumdar |
| 2024 | ICML | PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect. | Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh, Sunita Sarawagi |
| 2024 | ISIT | Detection of False Data Injection Attacks in Cyber-Physical Systems. | Souvik Das, Avishek Ghosh, Debasish Chatterjee |
| 2024 | ISIT | DIST-CURE: A Robust Distributed Learning Algorithm with Cubic Regularized Newton. | Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar |
| 2024 | ISIT | Explore-then-Commit Algorithms for Decentralized Two-Sided Matching Markets. | Tejas Pagare, Avishek Ghosh |
| 2023 | AISTATS | Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference. | Debangshu Banerjee, Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan |
| 2023 | ISIT | Optimal Compression of Unit Norm Vectors in the High Distortion Regime. | Heng Zhu, Avishek Ghosh, Arya Mazumdar |
| 2022 | ICML | Breaking the $\sqrt{T}$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits. | Avishek Ghosh, Abishek Sankararaman |
| 2022 | ICML | On Learning Mixture of Linear Regressions in the Non-Realizable Setting. | Soumyabrata Pal, Arya Mazumdar, Rajat Sen, Avishek Ghosh |
| 2021 | AISTATS | Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits. | Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran |
| 2021 | UAI | LocalNewton: Reducing communication rounds for distributed learning. | Vipul Gupta, Avishek Ghosh, Michal Derezinski, Rajiv Khanna, Kannan Ramchandran, Michael W. Mahoney |
| 2020 | AISTATS | Alternating Minimization Converges Super-Linearly for Mixed Linear Regression. | Avishek Ghosh, Kannan Ramchandran |
| 2020 | ISIT | Communication Efficient and Byzantine Tolerant Distributed Learning. | Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar, Kannan Ramchandran |
| 2020 | ISIT | Communication Efficient Distributed Approximate Newton Method. | Avishek Ghosh, Raj Kumar Maity, Arya Mazumdar, Kannan Ramchandran |
| 2020 | ISIT | Max-affine regression with universal parameter estimation for small-ball designs. | Avishek Ghosh, Ashwin Pananjady, Aditya Guntuboyina, Kannan Ramchandran |
| 2020 | ISIT | Some Performance Guarantees of Global LASSO with Local Assumptions for Convolutional Sparse Design Matrices. | Avishek Ghosh, Kannan Ramchandran |
| 2020 | ITA | Communication-Efficient and Byzantine-Robust Distributed Learning. | Avishek Ghosh, Raj Kumar Maity, Swanand Kadhe, Arya Mazumdar, Kannan Ramchandran |
| 2017 | AAAI | Misspecified Linear Bandits. | Avishek Ghosh, Sayak Ray Chowdhury, Aditya Gopalan |
| 2014 | MASS | Impromptu Deployment of Wireless Relay Networks: Experiences Along a Forest Trail. | Arpan Chattopadhyay, Avishek Ghosh, Akhila S. Rao, Bharat Dwivedi, S. V. R. Anand, Marceau Coupechoux, Anurag Kumar |
| 2012 | CEC | 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 |
| 2009 | ACL | Case markers and Morphology: Addressing the crux of the fluency problem in English-Hindi SMT. | Ananthakrishnan Ramanathan, Hansraj Choudhary, Avishek Ghosh, Pushpak Bhattacharyya |