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ORCIDParamveer S. Dhillon
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- affiliation: University of Michigan, MI, USA
- affiliation (PhD 2015): University of Pennsylvania, Computer and Information Science Department
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2020 – today
- 2026
[j13]Jie Cao, Emily Balczewski, Rahul Ladhania, Paramveer Dhillon, Donald S. Likosky
, Allison M. Janda, Nathan L. Pace, Robert E. Freundlich, Douglas A. Colquhoun, Bradley A. Fritz, Robert B. Schonberger, Sachin Kheterpal, Michael R. Mathis, Karandeep Singh:
Exploring the limits of localization: federated model stacking improves hospital-level prediction in a national research network. npj Digit. Medicine 9(1) (2026)- [c34]Katy Ilonka Gero, Tao Long, Carly Schnitzler, Paramveer Dhillon:
From Planning to Revision: How AI Writing Support at Different Stages Alters Ownership. DIS 2026: 2903-2934 - [c33]Tuhin Chakrabarty, Paramveer S. Dhillon:
Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High Quality Books. CHI 2026: 1432:1-1432:27 - [c32]Yachuan Liu, Xiaochun Wei, Lin Shi, Xinnuo Li, Bohan Zhang, Paramveer Dhillon, Qiaozhu Mei:
ExAnte: A Benchmark for Ex-Ante Inference in Large Language Models. EACL (Volume 1: Long Papers) 2026: 1551-1571 - [i19]Bohan Zhang, Chengke Bu, Paramveer S. Dhillon:
Who Owns the Text? Design Patterns for Preserving Authorship in AI-Assisted Writing. CoRR abs/2601.10236 (2026) - [i18]Tuhin Chakrabarty, Paramveer S. Dhillon:
Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High-Quality Books. CoRR abs/2601.18353 (2026) - [i17]Katy Ilonka Gero, Tao Long, Carly Schnitzler, Paramveer Dhillon:
From Planning to Revision: How AI Writing Support at Different Stages Alters Ownership. CoRR abs/2604.11009 (2026) - 2025
- [j12]Yulin Yu, Xianglong Li, Tianyi Li, Paramveer S. Dhillon, Daniel M. Romero:
Demographic disparity in Wikipedia coverage: a global perspective. EPJ Data Sci. 14(1): 15 (2025) - [j11]Yulin Yu, Houming Chen, Daniel M. Romero, Paramveer S. Dhillon:
Signals in the Noise: Decoding Unexpected Engagement Patterns on Twitter. Proc. ACM Hum. Comput. Interact. 9(7): 1-33 (2025) - [c31]Siqi Liang, Sumyeong Ahn, Paramveer Dhillon, Jiayu Zhou:
Dual Debiasing for Noisy In-Context Learning for Text Generation. ACL (Findings) 2025: 12855-12868 - [c30]Bohan Zhang, Yachuan Liu, Qiaozhu Mei, Paramveer S. Dhillon:
Leveraging Group-Level Signals for Robust Many-Domain Generalization. PAKDD (3) 2025: 195-209 - [c29]Md Sanzeed Anwar, Paramveer S. Dhillon, Grant Schoenebeck:
Recommendation and Temptation. RecSys 2025: 422-431 - [i16]Bohan Zhang, Yixin Wang, Paramveer S. Dhillon:
Policy Learning with a Natural Language Action Space: A Causal Approach. CoRR abs/2502.17538 (2025) - [i15]Yachuan Liu, Xiaochun Wei, Lin Shi, Xinnuo Li, Bohan Zhang, Paramveer Dhillon, Qiaozhu Mei:
ExAnte: A Benchmark for Ex-Ante Inference in Large Language Models. CoRR abs/2505.19533 (2025) - [i14]Siqi Liang, Sumyeong Ahn, Paramveer S. Dhillon, Jiayu Zhou:
Dual Debiasing for Noisy In-Context Learning for Text Generation. CoRR abs/2506.00418 (2025) - [i13]Yulin Yu, Houming Chen, Daniel M. Romero, Paramveer S. Dhillon:
Signals in the Noise: Decoding Unexpected Engagement Patterns on Twitter. CoRR abs/2509.08128 (2025) - [i12]Tuhin Chakrabarty, Jane C. Ginsburg, Paramveer Dhillon:
Readers Prefer Outputs of AI Trained on Copyrighted Books over Expert Human Writers. CoRR abs/2510.13939 (2025) - 2024
- [j10]Yachuan Liu, Jiaqi Ma, Paramveer Dhillon, Qiaozhu Mei:
PM2.5 forecasting under distribution shift: A graph learning approach. AI Open 5: 23-29 (2024) - [j9]Jeremy Yang, Dean Eckles, Paramveer Dhillon, Sinan Aral:
Targeting for Long-Term Outcomes. Manag. Sci. 70(6): 3841-3855 (2024) - [j8]Yulin Yu, Julie Jiang, Paramveer S. Dhillon:
Characterizing the Structure of Online Conversations Across Reddit. Proc. ACM Hum. Comput. Interact. 8(CSCW2): 1-23 (2024) - [c28]Paramveer S. Dhillon, Somayeh Molaei, Jiaqi Li, Maximilian Golub, Shaochun Zheng, Lionel Peter Robert:
Shaping Human-AI Collaboration: Varied Scaffolding Levels in Co-writing with Language Models. CHI 2024: 1044:1-1044:18 - [c27]Bohan Zhang, Yixin Wang, Paramveer Dhillon:
Causal Inference for Human-Language Model Collaboration. NAACL-HLT 2024: 1630-1647 - [c26]Md Sanzeed Anwar, Grant Schoenebeck, Paramveer S. Dhillon:
Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns. WWW 2024: 123-134 - [i11]Paramveer S. Dhillon, Somayeh Molaei, Jiaqi Li, Maximilian Golub, Shaochun Zheng, Lionel P. Robert:
Shaping Human-AI Collaboration: Varied Scaffolding Levels in Co-writing with Language Models. CoRR abs/2402.11723 (2024) - [i10]Md Sanzeed Anwar, Grant Schoenebeck, Paramveer S. Dhillon:
Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns. CoRR abs/2402.15013 (2024) - [i9]Bohan Zhang, Yixin Wang, Paramveer S. Dhillon:
Causal Inference for Human-Language Model Collaboration. CoRR abs/2404.00207 (2024) - [i8]Md Sanzeed Anwar, Paramveer S. Dhillon, Grant Schoenebeck:
Recommendation and Temptation. CoRR abs/2412.10595 (2024) - 2023
- [j7]Sinan Aral, Paramveer S. Dhillon:
What (Exactly) Is Novelty in Networks? Unpacking the Vision Advantages of Brokers, Bridges, and Weak Ties. Manag. Sci. 69(2): 1092-1115 (2023) - [c25]Yulin Yu, Pui Yin Cheung, Yong-Yeol Ahn, Paramveer S. Dhillon:
Unique in What Sense? Heterogeneous Relationships between Multiple Types of Uniqueness and Popularity in Music. ICWSM 2023: 914-925 - [i7]Yachuan Liu, Bohan Zhang, Qiaozhu Mei, Paramveer Dhillon:
Ranking & Reweighting Improves Group Distributional Robustness. CoRR abs/2305.05759 (2023) - 2022
- [c24]Evan Weissburg, Arya Kumar, Paramveer S. Dhillon:
Judging a Book by Its Cover: Predicting the Marginal Impact of Title on Reddit Post Popularity. ICWSM 2022: 1098-1108 - [c23]Barbara J. Ericson, Hisamitsu Maeda, Paramveer S. Dhillon:
Detecting Struggling Students from Interactive Ebook Data: A Case Study Using CSAwesome. SIGCSE (1) 2022: 418-424 - [c22]Yulin Yu, Yucong Hao, Paramveer Dhillon:
Unpacking Gender Stereotypes in Film Dialogue. SocInfo 2022: 398-405 - [i6]Yulin Yu, Pui Yin Cheung, Yong-Yeol Ahn, Paramveer Dhillon:
Unique in what sense? Heterogeneous relationships between multiple types of uniqueness and popularity in music. CoRR abs/2207.12943 (2022) - [i5]Yulin Yu, Paramveer Dhillon:
Deconstructing the structure of online conversations on Reddit. CoRR abs/2209.14836 (2022) - 2021
- [j6]Sinan Aral, Paramveer S. Dhillon:
Digital Paywall Design: Implications for Content Demand and Subscriptions. Manag. Sci. 67(4): 2381-2402 (2021) - [j5]Paramveer S. Dhillon, Sinan Aral:
Modeling Dynamic User Interests: A Neural Matrix Factorization Approach. Mark. Sci. 40(6): 1059-1080 (2021) - [c21]Hisamitsu Maeda, Barbara Ericson, Paramveer S. Dhillon:
Comparing Ebook Student Interactions With Test Scores: A Case Study Using CSAwesome (Work in Progress). EDM (Workshops) 2021 - [i4]Paramveer S. Dhillon, Sinan Aral:
Modeling Dynamic User Interests: A Neural Matrix Factorization Approach. CoRR abs/2102.06602 (2021) - [i3]Evan Weissburg, Arya Kumar, Paramveer S. Dhillon:
Judging a book by its cover: Predicting the marginal impact of title on Reddit post popularity. CoRR abs/2112.12191 (2021) - 2020
- [i2]Jeremy Yang, Dean Eckles, Paramveer S. Dhillon, Sinan Aral:
Targeting for long-term outcomes. CoRR abs/2010.15835 (2020)
2010 – 2019
- 2015
- [j4]Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar:
Eigenwords: spectral word embeddings. J. Mach. Learn. Res. 16: 3035-3078 (2015) - [e1]Phil Blunsom, Shay B. Cohen, Paramveer S. Dhillon, Percy Liang:
Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, VS@NAACL-HLT 2015, June 5, 2015, Denver, Colorado, USA. The Association for Computational Linguistics 2015, ISBN 978-1-941643-46-4 [contents] - 2014
- [j3]Paramveer S. Dhillon, David A. Wolk, Sandhitsu R. Das, Lyle H. Ungar, James C. Gee, Brian B. Avants:
Subject-specific functional parcellation via Prior Based Eigenanatomy. NeuroImage 99: 14-27 (2014) - 2013
- [j2]Paramveer S. Dhillon, Dean P. Foster, Sham M. Kakade, Lyle H. Ungar:
A risk comparison of ordinary least squares vs ridge regression. J. Mach. Learn. Res. 14(1): 1505-1511 (2013) - [c20]Paramveer S. Dhillon, Yichao Lu, Dean P. Foster, Lyle H. Ungar:
New Subsampling Algorithms for Fast Least Squares Regression. NIPS 2013: 360-368 - [c19]Yichao Lu, Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar:
Faster Ridge Regression via the Subsampled Randomized Hadamard Transform. NIPS 2013: 369-377 - [c18]Paramveer S. Dhillon, James C. Gee, Lyle H. Ungar, Brian B. Avants:
Anatomically-Constrained PCA for Image Parcellation. PRNI 2013: 25-28 - [c17]Julia Stoyanovich, Paramveer S. Dhillon, Susan B. Davidson, Brian Lyons:
Learning to explore scientific workflow repositories. SSDBM 2013: 31:1-31:4 - 2012
- [c16]Paramveer S. Dhillon, Partha Pratim Talukdar, Koby Crammer:
Metric Learning for Graph-Based Domain Adaptation. COLING (Posters) 2012: 255-264 - [c15]Paramveer S. Dhillon, Jordan Rodu, Michael Collins, Dean P. Foster, Lyle H. Ungar:
Spectral Dependency Parsing with Latent Variables. EMNLP-CoNLL 2012: 205-213 - [c14]Paramveer S. Dhillon, Jordan Rodu, Dean P. Foster, Lyle H. Ungar:
Using CCA to improve CCA: A new spectral method for estimating vector models of words. ICML 2012 - [c13]Paramveer S. Dhillon, Brian B. Avants, Lyle H. Ungar, James C. Gee:
Partial sparse canonical correlation analysis (PSCCA) for population studies in medical imaging. ISBI 2012: 1132-1135 - [c12]Brian B. Avants, Paramveer S. Dhillon, Benjamin M. Kandel, Philip A. Cook, Corey McMillan, Murray Grossman, James C. Gee:
Eigenanatomy Improves Detection Power for Longitudinal Cortical Change. MICCAI (3) 2012: 206-213 - [c11]Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, Sundararajan Sellamanickam:
Deterministic Annealing for Semi-Supervised Structured Output Learning. AISTATS 2012: 299-307 - 2011
- [j1]Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar:
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning. J. Mach. Learn. Res. 12: 525-564 (2011) - [c10]Paramveer S. Dhillon, Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj:
Semi-supervised multi-task learning of structured prediction models for web information extraction. CIKM 2011: 957-966 - [c9]Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar:
Multi-View Learning of Word Embeddings via CCA. NIPS 2011: 199-207 - 2010
- [c8]Paramveer S. Dhillon, Partha Pratim Talukdar, Koby Crammer:
Learning Better Data Representation Using Inference-Driven Metric Learning. ACL (2) 2010: 377-381 - [c7]Rushin Shah, Paramveer S. Dhillon, Mark Y. Liberman, Dean P. Foster, Mohamed Maamouri, Lyle H. Ungar:
A New Approach to Lexical Disambiguation of Arabic Text. EMNLP 2010: 725-735 - [c6]Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar:
Feature Selection using Multiple Streams. AISTATS 2010: 153-160
2000 – 2009
- 2009
- [c5]Paramveer S. Dhillon, Lyle H. Ungar:
Transfer Learning, Feature Selection and Word Sense Disambiguation. ACL/IJCNLP (2) 2009: 257-260 - [c4]Paramveer S. Dhillon:
Robust Real-Time Face Tracking Using an Active Camera. CISIS 2009: 179-186 - [c3]Paramveer S. Dhillon, Sebastian Nowozin, Christoph H. Lampert:
Combining appearance and motion for human action classification in videos. CVPR Workshops 2009: 22-29 - [c2]Paramveer S. Dhillon, Brian Tomasik, Dean P. Foster, Lyle H. Ungar:
Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC). ECML/PKDD (1) 2009: 276-289 - [i1]Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar:
Transfer Learning Using Feature Selection. CoRR abs/0905.4022 (2009) - 2008
- [c1]Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar:
Efficient Feature Selection in the Presence of Multiple Feature Classes. ICDM 2008: 779-784
Coauthor Index
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last updated on 2026-07-20 02:25 CEST by the dblp team
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