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2020 – today
- 2024
[j2]Jifan Zhang, Salih Tutun, Samira Fazel Anvaryazdi, Mohammadhossein Amini, Durai Sundaramoorthi
, Hema Sundaramoorthi:
Management of resource sharing in emergency response using data-driven analytics. Ann. Oper. Res. 339(1-2): 663-692 (2024)- [j1]Nasim Soltani, Jifan Zhang, Batool Salehi, Debashri Roy, Robert D. Nowak, Kaushik R. Chowdhury:
Learning from the Best: Active Learning for Wireless Communications. IEEE Wirel. Commun. 31(4): 177-183 (2024) - [c5]Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeff A. Bilmes, Simon S. Du, Kevin G. Jamieson, Jordan T. Ash, Robert D. Nowak:
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. ACL (Findings) 2024: 6549-6560 - [i11]Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeffrey A. Bilmes, Simon S. Du, Kevin G. Jamieson, Jordan T. Ash, Robert D. Nowak:
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. CoRR abs/2401.06692 (2024) - [i10]Nasim Soltani, Jifan Zhang, Batool Salehi, Debashri Roy, Robert D. Nowak, Kaushik R. Chowdhury:
Learning from the Best: Active Learning for Wireless Communications. CoRR abs/2402.04896 (2024) - [i9]Jifan Zhang, Lalit Jain, Yang Guo, Jiayi Chen, Kuan Lok Zhou, Siddharth Suresh, Andrew Wagenmaker, Scott Sievert, Timothy T. Rogers, Kevin Jamieson, Robert Mankoff, Robert Nowak:
Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning. CoRR abs/2406.10522 (2024) - [i8]Jifan Zhang, Robert D. Nowak:
SIEVE: General Purpose Data Filtering System Matching GPT-4o Accuracy at 1% the Cost. CoRR abs/2410.02755 (2024) - 2023
- [c4]Jifan Zhang, Zhe Wu, Xinfeng Zhang, Guoli Song, Yaowei Wang, Jie Chen:
Recurrent Fine-Grained Self-Attention Network for Video Crowd Counting. ICASSP 2023: 1-5 - [c3]Jifan Zhang, Shuai Shao, Saurabh Verma, Robert D. Nowak:
Algorithm Selection for Deep Active Learning with Imbalanced Datasets. NeurIPS 2023 - [i7]Jifan Zhang, Shuai Shao, Saurabh Verma, Robert D. Nowak:
Algorithm Selection for Deep Active Learning with Imbalanced Datasets. CoRR abs/2302.07317 (2023) - [i6]Jifan Zhang, Yifang Chen, Gregory Canal, Stephen Mussmann, Yinglun Zhu, Simon Shaolei Du, Kevin G. Jamieson, Robert D. Nowak:
LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning. CoRR abs/2306.09910 (2023) - [i5]Shyam Nuggehalli, Jifan Zhang, Lalit Jain, Robert D. Nowak:
DIRECT: Deep Active Learning under Imbalance and Label Noise. CoRR abs/2312.09196 (2023) - 2022
- [c2]Jifan Zhang, Julian Katz-Samuels, Robert D. Nowak:
GALAXY: Graph-based Active Learning at the Extreme. ICML 2022: 26223-26238 - [i4]Jifan Zhang, Julian Katz-Samuels, Robert D. Nowak:
GALAXY: Graph-based Active Learning at the Extreme. CoRR abs/2202.01402 (2022) - [i3]Liu Yang, Jifan Zhang, Joseph Shenouda, Dimitris S. Papailiopoulos, Kangwook Lee, Robert D. Nowak:
A Better Way to Decay: Proximal Gradient Training Algorithms for Neural Nets. CoRR abs/2210.03069 (2022) - 2021
- [c1]Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson:
Improved Algorithms for Agnostic Pool-based Active Classification. ICML 2021: 5334-5344 - [i2]Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson:
Improved Algorithms for Agnostic Pool-based Active Classification. CoRR abs/2105.06499 (2021) - 2020
- [i1]Jifan Zhang, Kevin Jamieson:
Learning to Actively Learn: A Robust Approach. CoRR abs/2010.15382 (2020)
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