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ORCIDArpit Agarwal
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2020 – today
- 2024
[c33]William Brown, Arpit Agarwal:
Online Recommendations for Agents with Discounted Adaptive Preferences. ALT 2024: 244-281- [c32]Arpit Agarwal
, Nicolas Usunier, Alessandro Lazaric, Maximilian Nickel:
System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes. FAccT 2024: 1763-1773 - [c31]Yuxiang Ma, Arpit Agarwal, Sandra Q. Liu, Wenzhen Yuan, Edward H. Adelson:
Scalable Simulation-Guided Compliant Tactile Finger Design. RoboSoft 2024: 1068-1074 - [c30]Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil, Chen Wang, Nathan White, Peilin Zhong:
Parallel Approximate Maximum Flows in Near-Linear Work and Polylogarithmic Depth. SODA 2024: 3997-4061 - [i24]Arpit Agarwal, Rad Niazadeh, Prathamesh Patil:
Misalignment, Learning, and Ranking: Harnessing Users Limited Attention. CoRR abs/2402.14013 (2024) - [i23]Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil, Chen Wang, Nathan White, Peilin Zhong:
Parallel Approximate Maximum Flows in Near-Linear Work and Polylogarithmic Depth. CoRR abs/2402.14950 (2024) - [i22]Yuxiang Ma, Arpit Agarwal, Sandra Q. Liu, Wenzhen Yuan, Edward H. Adelson:
Scalable, Simulation-Guided Compliant Tactile Finger Design. CoRR abs/2403.04638 (2024) - [i21]Joe Suk, Arpit Agarwal:
Optimal and Adaptive Non-Stationary Dueling Bandits Under a Generalized Borda Criterion. CoRR abs/2403.12950 (2024) - [i20]Arpit Agarwal, Nicolas Usunier, Alessandro Lazaric, Maximilian Nickel:
System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes. CoRR abs/2406.01611 (2024) - 2023
- [c29]Arpit Agarwal, Abhiroop Ajith, Chengtao Wen, Veniamin Stryzheus, Brian Miller, Matthew Chen, Micah K. Johnson, Jose Luis Susa Rincon, Justinian Rosca, Wenzhen Yuan:
Robotic Defect Inspection with Visual and Tactile Perception for Large-Scale Components. IROS 2023: 10110-10116 - [c28]Joe Suk, Arpit Agarwal:
When Can We Track Significant Preference Shifts in Dueling Bandits? NeurIPS 2023 - [i19]Arpit Agarwal, William Brown:
Online Recommendations for Agents with Discounted Adaptive Preferences. CoRR abs/2302.06014 (2023) - [i18]Joe Suk, Arpit Agarwal:
When Can We Track Significant Preference Shifts in Dueling Bandits? CoRR abs/2302.06595 (2023) - [i17]Arpit Agarwal, Abhiroop Ajith, Chengtao Wen, Veniamin Stryzheus, Brian Miller, Matthew Chen, Micah K. Johnson, Jose Luis Susa Rincon, Justinian Rosca, Wenzhen Yuan:
Robotic Defect Inspection with Visual and Tactile Perception for Large-scale Components. CoRR abs/2309.04590 (2023) - [i16]Arpit Agarwal, Eric Balkanski:
Learning-Augmented Dynamic Submodular Maximization. CoRR abs/2311.13006 (2023) - [i15]Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan:
Semi-Bandit Learning for Monotone Stochastic Optimization. CoRR abs/2312.15427 (2023) - 2022
- [c27]Arpit Agarwal, Sanjeev Khanna, Prathamesh Patil:
PAC Top-k Identification under SST in Limited Rounds. AISTATS 2022: 6814-6839 - [c26]Arpit Agarwal, Sanjeev Khanna, Prathamesh Patil:
A Sharp Memory-Regret Trade-off for Multi-Pass Streaming Bandits. COLT 2022: 1423-1462 - [c25]Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan:
Batched Dueling Bandits. ICML 2022: 89-110 - [c24]Divyansh Rai, Arpit Agarwal, Bagesh Kumar, O. P. Vyas, Suhaib Khan, S. Shourya:
Generating Textual Description Using Modified Beam Search. ICONIP (5) 2022: 136-147 - [c23]Zilin Si, Zirui Zhu, Arpit Agarwal, Stuart Anderson, Wenzhen Yuan:
Grasp Stability Prediction with Sim-to-Real Transfer from Tactile Sensing. IROS 2022: 7809-7816 - [c22]Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan:
An Asymptotically Optimal Batched Algorithm for the Dueling Bandit Problem. NeurIPS 2022 - [c21]Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil:
Sublinear Algorithms for Hierarchical Clustering. NeurIPS 2022 - [c20]William Brown, Arpit Agarwal:
Diversified Recommendations for Agents with Adaptive Preferences. NeurIPS 2022 - [i14]Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan:
Batched Dueling Bandits. CoRR abs/2202.10660 (2022) - [i13]Arpit Agarwal, Sanjeev Khanna, Prathamesh Patil:
A Sharp Memory-Regret Trade-Off for Multi-Pass Streaming Bandits. CoRR abs/2205.00984 (2022) - [i12]Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil:
Sublinear Algorithms for Hierarchical Clustering. CoRR abs/2206.07633 (2022) - [i11]Zilin Si, Zirui Zhu, Arpit Agarwal, Stuart Anderson, Wenzhen Yuan:
Grasp Stability Prediction with Sim-to-Real Transfer from Tactile Sensing. CoRR abs/2208.02885 (2022) - [i10]Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan:
An Asymptotically Optimal Batched Algorithm for the Dueling Bandit Problem. CoRR abs/2209.12108 (2022) - [i9]Arpit Agarwal, William Brown:
Diversified Recommendations for Agents with Adaptive Preferences. CoRR abs/2210.07773 (2022) - 2021
- [j2]Prabhu Ramachandran, Aditya Bhosale, Kunal Puri, Pawan Negi, Abhinav Muta, A. Dinesh, Dileep Menon, Rahul Govind, Suraj Sanka, Amal S. Sebastian, Ananyo Sen, Rohan Kaushik, Anshuman Kumar, Vikas Kurapati, Mrinalgouda Patil, Deep Tavker, Pankaj Pandey, Chandrashekhar Kaushik, Arkopal Dutt, Arpit Agarwal:
PySPH: A Python-based Framework for Smoothed Particle Hydrodynamics. ACM Trans. Math. Softw. 47(4): 34:1-34:38 (2021) - [c19]Arpit Agarwal, Shivani Agarwal, Prathamesh Patil:
Stochastic Dueling Bandits with Adversarial Corruption. ALT 2021: 217-248 - [c18]Arpit Agarwal, Timothy Man, Wenzhen Yuan:
Simulation of Vision-based Tactile Sensors using Physics based Rendering. ICRA 2021: 1-7 - [c17]Raj Kolamuri, Zilin Si, Yufan Zhang, Arpit Agarwal, Wenzhen Yuan:
Improving Grasp Stability with Rotation Measurement from Tactile Sensing. IROS 2021: 6809-6816 - [i8]Raj Kolamuri, Zilin Si, Yufan Zhang, Arpit Agarwal, Wenzhen Yuan:
Improving Grasp Stability with Rotation Measurement from Tactile Sensing. CoRR abs/2108.00301 (2021) - [i7]Arpit Agarwal:
Machine learning models for prediction of droplet collision outcomes. CoRR abs/2110.00167 (2021) - 2020
- [j1]Arpit Agarwal, Debmalya Mandal, David C. Parkes, Nisarg Shah:
Peer Prediction with Heterogeneous Users. ACM Trans. Economics and Comput. 8(1): 2:1-2:34 (2020) - [c16]Arpit Agarwal, Shivani Agarwal, Sanjeev Khanna, Prathamesh Patil:
Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions. ICML 2020: 85-95 - [c15]Arpit Agarwal, Nicholas Johnson, Shivani Agarwal:
Choice Bandits. NeurIPS 2020 - [i6]Arpit Agarwal, Tim Man, Wenzhen Yuan:
Simulation of Vision-based Tactile Sensors using Physics based Rendering. CoRR abs/2012.13184 (2020)
2010 – 2019
- 2019
- [c14]Arpit Agarwal, Katharina Muelling, Katerina Fragkiadaki:
Model Learning for Look-Ahead Exploration in Continuous Control. AAAI 2019: 3151-3158 - [c13]Arpit Agarwal, Sepehr Assadi, Sanjeev Khanna:
Stochastic Submodular Cover with Limited Adaptivity. SODA 2019: 323-342 - [i5]Prabhu Ramachandran, Kunal Puri, Aditya Bhosale, A. Dinesh, Abhinav Muta, Pawan Negi, Rahul Govind, Suraj Sanka, Pankaj Pandey, Chandrashekhar Kaushik, Anshuman Kumar, Ananyo Sen, Rohan Kaushik, Mrinalgouda Patil, Deep Tavker, Dileep Menon, Vikas Kurapati, Amal S. Sebastian, Arkopal Dutt, Arpit Agarwal:
PySPH: a Python-based framework for smoothed particle hydrodynamics. CoRR abs/1909.04504 (2019) - 2018
- [c12]Ricson Cheng, Arpit Agarwal, Katerina Fragkiadaki:
Reinforcement Learning of Active Vision for Manipulating Objects under Occlusions. CoRL 2018: 422-431 - [c11]Arpit Agarwal, Prathamesh Patil, Shivani Agarwal:
Accelerated Spectral Ranking. ICML 2018: 70-79 - [i4]Arpit Agarwal, Sepehr Assadi, Sanjeev Khanna:
Stochastic Submodular Cover with Limited Adaptivity. CoRR abs/1810.13351 (2018) - [i3]Ricson Cheng, Arpit Agarwal, Katerina Fragkiadaki:
Reinforcement Learning of Active Vision forManipulating Objects under Occlusions. CoRR abs/1811.08067 (2018) - [i2]Arpit Agarwal, Katharina Muelling, Katerina Fragkiadaki:
Model Learning for Look-ahead Exploration in Continuous Control. CoRR abs/1811.08086 (2018) - 2017
- [c10]Arpit Agarwal, Shivani Agarwal, Sepehr Assadi, Sanjeev Khanna:
Learning with Limited Rounds of Adaptivity: Coin Tossing, Multi-Armed Bandits, and Ranking from Pairwise Comparisons. COLT 2017: 39-75 - [c9]Arpit Agarwal, Debmalya Mandal, David C. Parkes, Nisarg Shah:
Peer Prediction with Heterogeneous Users. EC 2017: 81-98 - 2016
- [c8]Victor Shnayder, Arpit Agarwal, Rafael M. Frongillo, David C. Parkes:
Informed Truthfulness in Multi-Task Peer Prediction. EC 2016: 179-196 - [c7]Rohan Raj Gupta, Gaurav Mishra, Subham Katara, Arpit Agarwal, Mrinal Kanti Sarkar, Rupayan Das, Sanjay Kumar:
Data storage security in cloud computing using container clustering. UEMCON 2016: 1-7 - [i1]Victor Shnayder, Arpit Agarwal, Rafael M. Frongillo, David C. Parkes:
Informed Truthfulness in Multi-Task Peer Prediction. CoRR abs/1603.03151 (2016) - 2015
- [c6]Arpit Agarwal, Shivani Agarwal:
On Consistent Surrogate Risk Minimization and Property Elicitation. COLT 2015: 4-22 - 2014
- [c5]Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan, Shivani Agarwal:
GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare. ICML 2014: 1989-1997 - 2013
- [c4]Arpit Agarwal, Ritu Garg, Santanu Chaudhury:
Greedy Search for Active Learning of OCR. ICDAR 2013: 837-841 - 2012
- [c3]Shengdong Zhao, Fanny Chevalier, Wei Tsang Ooi, Chee Yuan Lee, Arpit Agarwal:
AutoComPaste: auto-completing text as an alternative to copy-paste. AVI 2012: 365-372 - 2011
- [c2]Arpit Agarwal, Rahul Banerjee, Varun Pandey, Riya Charaya:
An Optimal Human Adaptive Algorithm to Find Action - Reaction Word-Pairs. HCI (22) 2011: 255-259 - [c1]Brad Calder, Ju Wang, Aaron Ogus, Niranjan Nilakantan, Arild Skjolsvold, Sam McKelvie, Yikang Xu, Shashwat Srivastav, Jiesheng Wu, Huseyin Simitci, Jaidev Haridas, Chakravarthy Uddaraju, Hemal Khatri, Andrew Edwards, Vaman Bedekar, Shane Mainali, Rafay Abbasi, Arpit Agarwal, Mian Fahim ul Haq, Muhammad Ikram ul Haq, Deepali Bhardwaj, Sowmya Dayanand, Anitha Adusumilli, Marvin McNett, Sriram Sankaran, Kavitha Manivannan, Leonidas Rigas:
Windows Azure Storage: a highly available cloud storage service with strong consistency. SOSP 2011: 143-157
Coauthor Index
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last updated on 2024-10-07 21:25 CEST by the dblp team
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