Input-Output Logic based Fault-Tolerant Design Technique for SRAM-based FPGAs. - Aditya Srinivas Timmaraju; Aniket Anand Deshmukh; Mohammed Amir Khan; Zafar Ali Khan (CoRR, 2013)

Multi-Task Learning for Contextual Bandits. - Aniket Anand Deshmukh; Ürün Dogan; Clayton Scott (NIPS, 2017)

Semi-Supervised Transfer Learning Using Marginal Predictors. - Aniket Anand Deshmukh; Emil Laftchiev (DSW, 2018)

Domain2Vec: Deep Domain Generalization. - Aniket Anand Deshmukh; Ankit Bansal; Akash Rastogi (CoRR, 2018)

Simple Regret Minimization for Contextual Bandits. - Aniket Anand Deshmukh; Srinagesh Sharma; James W. Cutler; Mark Moldwin; Clayton Scott (CoRR, 2018)

A Generalization Error Bound for Multi-class Domain Generalization. - Aniket Anand Deshmukh; Yunwen Lei; Srinagesh Sharma; Ürün Dogan; James W. Cutler; Clayton Scott (CoRR, 2019)

PAC Reinforcement Learning without Real-World Feedback. - Yuren Zhong; Aniket Anand Deshmukh; Clayton Scott (CoRR, 2019)

Zero-Shot Domain Generalization. - Udit Maniyar; K. J. Joseph; Aniket Anand Deshmukh; Ürün Dogan; Vineeth N. Balasubramanian (BMVC, 2020)

Label-Similarity Curriculum Learning. - Ürün Dogan; Aniket Anand Deshmukh; Marcin Machura; Christian Igel (ECCV (29), 2020)

Head and Tail Localization of C. elegans. - Mansi Ranjit Mane; Aniket Anand Deshmukh; Adam J. Iliff (CoRR, 2020)

Data Transformation Insights in Self-supervision with Clustering Tasks. - Abhimanu Kumar; Aniket Anand Deshmukh; Ürün Dogan; Denis Charles; Eren Manavoglu (CoRR, 2020)

Self-Supervised Contextual Bandits in Computer Vision. - Aniket Anand Deshmukh; Abhimanu Kumar; Levi Boyles; Denis Charles; Eren Manavoglu; Ürün Dogan (CoRR, 2020)

Consensus Clustering With Unsupervised Representation Learning. - Jayanth Reddy Regatti; Aniket Anand Deshmukh; Eren Manavoglu; Ürün Dogan (IJCNN, 2021)

On Challenges in Unsupervised Domain Generalization. - Vaasudev Narayanan; Aniket Anand Deshmukh; Ürün Dogan; Vineeth N. Balasubramanian (Pre-Registration Workshop @ NeurIPS, 2021)

Offline RL With Resource Constrained Online Deployment. - Jayanth Reddy Regatti; Aniket Anand Deshmukh; Frank Cheng; Young Hun Jung; Abhishek Gupta 002; Ürün Dogan (CoRR, 2021)

Domain Generalization by Marginal Transfer Learning. - Gilles Blanchard; Aniket Anand Deshmukh; Ürün Dogan; Gyemin Lee; Clayton Scott (J. Mach. Learn. Res., 2021)

Representation learning for clustering via building consensus. - Aniket Anand Deshmukh; Jayanth Reddy Regatti; Eren Manavoglu; Ürün Dogan (Mach. Learn., 2022)

Foreword for Workshop on Decision Making for Information Retrieval and Recommender Systems. - Da Xu; Tobias Schnabel; Xiquan Cui; Sarah Dean; Aniket Deshmukh 001; Bo Yang; Shipeng Yu (WWW (Companion Volume), 2023)

First Workshop on Generative AI for Recommender Systems and Personalization. - Narges Tabari; Aniket Anand Deshmukh; Wang-Cheng Kang; Hamed Zamani; Rashmi Gangadharaiah; Julian J. McAuley; George Karypis (KDD, 2024)

Online Posterior Sampling with a Diffusion Prior. - Branislav Kveton; Boris Oreshkin; Youngsuk Park; Aniket Deshmukh 001; Rui Song 006 (NeurIPS, 2024)

Optimal Design for Human Preference Elicitation. - Subhojyoti Mukherjee; Anusha Lalitha; Kousha Kalantari; Aniket Deshmukh 001; Ge Liu; Yifei Ma; Branislav Kveton (NeurIPS, 2024)

Experimental Design for Active Transductive Inference in Large Language Models. - Subhojyoti Mukherjee; Ge Liu; Aniket Deshmukh 001; Anusha Lalitha; Yifei Ma; Branislav Kveton (CoRR, 2024)

Optimal Design for Human Feedback. - Subhojyoti Mukherjee; Anusha Lalitha; Kousha Kalantari; Aniket Deshmukh 001; Ge Liu; Yifei Ma; Branislav Kveton (CoRR, 2024)

Multi-Objective Alignment of Large Language Models Through Hypervolume Maximization. - Subhojyoti Mukherjee; Anusha Lalitha; Sailik Sengupta; Aniket Deshmukh 001; Branislav Kveton (CoRR, 2024)