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Author search results
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- Nikhil Garg — disambiguation page
- Nikhil Garg 0001
Cornell Tech, NY, USA - Nikhil Garg 0002
University of Sherbrooke, QC, Canada - Nikhil Garg 0003
University of Geneva, Switzerland - Nikhil Garg 0005
Ecole Polytechnique Fédérale de Lausanne, Switzerland
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Publication search results
found 178 matches
- 2024
- Vipin Kumar, Amit Kumar Gupta, Ruchi Rani Garg, Nikhil Kumar, Rajeev Kumar:
The ultimate recommendation system: proposed Pranik System. Multim. Tools Appl. 83(14): 43177-43198 (2024) - Zhi Liu, Uma Bhandaram, Nikhil Garg:
Quantifying spatial under-reporting disparities in resident crowdsourcing. Nat. Comput. Sci. 4(1): 57-65 (2024) - Nikhil Varma Keetha, Avneesh Mishra, Jay Karhade, Krishna Murthy Jatavallabhula, Sebastian A. Scherer, K. Madhava Krishna, Sourav Garg:
AnyLoc: Towards Universal Visual Place Recognition. IEEE Robotics Autom. Lett. 9(2): 1286-1293 (2024) - Sachin Kumar, Kartikey Saran, Yashu Garg, Gaurav Dubey, Shivam Goel, Alok Nikhil Jha, Ajit Kumar Verma:
A novel influence quantification model on Instagram using data science approach for targeted business advertising and better digital marketing outcomes. Soc. Netw. Anal. Min. 14(1): 71 (2024) - Nikhil Laxminarayana, Nimish Mishra, Prayag Tiwari, Sahil Garg, Bikash K. Behera, Ahmed Farouk:
Quantum-Assisted Activation for Supervised Learning in Healthcare-Based Intrusion Detection Systems. IEEE Trans. Artif. Intell. 5(3): 977-984 (2024) - Krati Mittal, Akash Gupta, Nikhil Sharma, Manan Jani, Parul Garg:
Performance Analysis of Hybrid RF/VLC Energy Harvested Terrestrial-Underwater System. IEEE Trans. Sustain. Comput. 9(3): 512-521 (2024) - Gabriel Agostini, Emma Pierson, Nikhil Garg:
A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing. AAAI 2024: 21888-21896 - Zhi Liu, Sarah Rankin, Nikhil Garg:
Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling. AAAI 2024: 22258-22265 - Sidhika Balachandar, Nikhil Garg, Emma Pierson:
Domain constraints improve risk prediction when outcome data is missing. ICLR 2024 - Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA 2024: 6892-6903 - Tyler Menezes, Lola Egherman, Nikhil Garg:
AI-Grading Standup Updates to Improve Project-Based Learning Outcomes. ITiCSE (1) 2024 - Rajiv Movva, Sidhika Balachandar, Kenny Peng, Gabriel Agostini, Nikhil Garg, Emma Pierson:
Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers. NAACL-HLT 2024: 1223-1243 - Kenny Peng, Manish Raghavan, Emma Pierson, Jon M. Kleinberg, Nikhil Garg:
Reconciling the Accuracy-Diversity Trade-off in Recommendations. WWW 2024: 1318-1329 - Kenny Peng, Nikhil Garg:
Wisdom and Foolishness of Noisy Matching Markets. CoRR abs/2402.16771 (2024) - Evan Dong, Aaron Schein, Yixin Wang, Nikhil Garg:
Addressing Discretization-Induced Bias in Demographic Prediction. CoRR abs/2405.16762 (2024) - Nikhil Garg, Davide Florini, Patrick Dufour, Eloi Muhr, Mathieu-Coumba Faye, Marc Bocquet, Damien Querlioz, Yann Beilliard, Dominique Drouin, Fabien Alibart, Jean-Michel Portal:
Versatile CMOS Analog LIF Neuron for Memristor-Integrated Neuromorphic Circuits. CoRR abs/2406.19667 (2024) - Alfredo Torrico, Natthawut Boonsiriphatthanajaroen, Nikhil Garg, Andrea Lodi, Hugo Mainguy:
Equitable Congestion Pricing under the Markovian Traffic Model: An Application to Bogota. CoRR abs/2407.05035 (2024) - Jinsook Lee, Emma Harvey, Joyce Zhou, Nikhil Garg, Thorsten Joachims, René F. Kizilcec:
Algorithms for College Admissions Decision Support: Impacts of Policy Change and Inherent Variability. CoRR abs/2407.11199 (2024) - Sanyukta Deshpande, Nikhil Garg, Sheldon H. Jacobson:
Optimal Strategies in Ranked Choice Voting. CoRR abs/2407.13661 (2024) - 2023
- Nikhila Kathirisetty, Rajendrasinh Jadeja, Hiren Kumar Thakkar, Deepak Garg, Cheng-Chieh Chang, Rajesh Mahadeva, Shashikant P. Patole:
Student Placement Probabilistic Assessment Using Emotional Quotient With Machine Learning: A Conceptual Case Study. IEEE Access 11: 125716-125737 (2023) - Gaspard Goupy, Alexandre Juneau-Fecteau, Nikhil Garg, Ismael Balafrej, Fabien Alibart, Luc Frechette, Dominique Drouin, Yann Beilliard:
Unsupervised and efficient learning in sparsely activated convolutional spiking neural networks enabled by voltage-dependent synaptic plasticity. Neuromorph. Comput. Eng. 3(1): 14001 (2023) - Mansi Goel, Shashank Dargar, Shounak Ghatak, Nidhi Verma, Pratik Chauhan, Anushka Gupta, Nikhila Vishnumolakala, Hareesh Amuru, Ekta Gambhir, Ronak Chhajed, Meenal Jain, Astha Jain, Samiksha Garg, Ganesh Bagler:
Dish Detection in Indian Food Platters: A Computational Framework for Diet Management. CVIP (1) 2023: 231-243 - Uddeshaya Kumar, Yogesh Pal, Perla Sai Nikhil, Manish Garg, M. Ranjith Kumar, Dharminder Chaudhary:
A Construction of Three Party Post Quantum Secure Authenticated Key Exchange for Mobile Users. ICCCNT 2023: 1-7 - Gal Kaplun, Nikhil Ghosh, Saurabh Garg, Boaz Barak, Preetum Nakkiran:
Deconstructing Distributions: A Pointwise Framework of Learning. ICLR 2023 - Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John V. Guttag, Nikhil Garg, Emma Pierson:
Coarse race data conceals disparities in clinical risk score performance. MLHC 2023: 443-472 - Meena Jagadeesan, Nikhil Garg, Jacob Steinhardt:
Supply-Side Equilibria in Recommender Systems. NeurIPS 2023 - Rana Shahout, Yehonatan Peisakhovsky, Sasha Stoikov, Nikhil Garg:
Interface Design to Mitigate Inflation in Recommender Systems. RecSys 2023: 897-903 - Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John V. Guttag, Nikhil Garg, Emma Pierson:
Coarse race data conceals disparities in clinical risk score performance. CoRR abs/2304.09270 (2023) - Mansi Goel, Shashank Dargar, Shounak Ghatak, Nidhi Verma, Pratik Chauhan, Anushka Gupta, Nikhila Vishnumolakala, Hareesh Amuru, Ekta Gambhir, Ronak Chhajed, Meenal Jain, Astha Jain, Samiksha Garg, Nitesh Narwade, Nikhilesh Verhwani, Abhuday Tiwari, Kirti Vashishtha, Ganesh Bagler:
Dish detection in food platters: A framework for automated diet logging and nutrition management. CoRR abs/2305.07552 (2023) - Smitha Milli, Emma Pierson, Nikhil Garg:
Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems. CoRR abs/2305.17428 (2023)
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