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2020 – today
- 2024
[c35]Munshi Mahbubur Rahman
, Shimei Pan, James R. Foulds:
Towards A Unifying Human-Centered AI Fairness Framework. GoodIT 2024: 88-92- [c34]Rashidul Islam, Shimei Pan, James R. Foulds:
Fair Inference for Discrete Latent Variable Models: An Intersectional Approach. GoodIT 2024: 188-196 - [c33]Philip Feldman, Aaron Dant, James R. Foulds:
Killer Apps: Low-Speed, Large-Scale AI Weapons. IUI Workshops 2024 - [i25]Philip Feldman, Aaron Dant, James R. Foulds:
Killer Apps: Low-Speed, Large-Scale AI Weapons. CoRR abs/2402.01663 (2024) - [i24]Philip Feldman, James R. Foulds, Shimei Pan:
RAGged Edges: The Double-Edged Sword of Retrieval-Augmented Chatbots. CoRR abs/2403.01193 (2024) - 2023
- [j10]Rashidul Islam, Kamrun Naher Keya, Shimei Pan, Anand D. Sarwate, James R. Foulds:
Differential Fairness: An Intersectional Framework for Fair AI. Entropy 25(4): 660 (2023) - [j9]Clarice Wang, Kathryn Wang, Andrew Bian, Rashidul Islam, Kamrun Naher Keya, James R. Foulds, Shimei Pan:
When Biased Humans Meet Debiased AI: A Case Study in College Major Recommendation. ACM Trans. Interact. Intell. Syst. 13(3): 17:1-17:28 (2023) - [c32]Philip Feldman, Shimei Pan, James R. Foulds:
The Keyword Explorer Suite: A Toolkit for Understanding Online Populations. IUI Companion 2023: 21-24 - [i23]Philip Feldman, Shimei Pan, James R. Foulds:
The Keyword Explorer Suite: A Toolkit for Understanding Online Populations. CoRR abs/2301.05198 (2023) - [i22]Philip Feldman, James R. Foulds, Shimei Pan:
Trapping LLM Hallucinations Using Tagged Context Prompts. CoRR abs/2306.06085 (2023) - [i21]Fatema Hasan, Yulong Li, James R. Foulds, Shimei Pan, Bishwaranjan Bhattacharjee:
Teach me with a Whisper: Enhancing Large Language Models for Analyzing Spoken Transcripts using Speech Embeddings. CoRR abs/2311.07014 (2023) - 2022
- [j8]Kamrun Naher Keya, Yannis Papanikolaou, James R. Foulds:
Neural Embedding Allocation: Distributed Representations of Topic Models. Comput. Linguistics 48(4): 1021-1052 (2022) - [c31]Clarice Wang, Kathryn Wang, Andrew Bian, Rashidul Islam, Kamrun Naher Keya, James R. Foulds, Shimei Pan:
Do Humans Prefer Debiased AI Algorithms? A Case Study in Career Recommendation. IUI 2022: 134-147 - [i20]Philip Feldman, Aaron Dant, James R. Foulds, Shimei Pan:
Polling Latent Opinions: A Method for Computational Sociolinguistics Using Transformer Language Models. CoRR abs/2204.07483 (2022) - [i19]George J. Cancro, Shimei Pan, James R. Foulds:
Tell Me Something That Will Help Me Trust You: A Survey of Trust Calibration in Human-Agent Interaction. CoRR abs/2205.02987 (2022) - [i18]Rashidul Islam, Shimei Pan, James R. Foulds:
Fair Inference for Discrete Latent Variable Models. CoRR abs/2209.07044 (2022) - 2021
- [j7]Shimei Pan, James R. Foulds:
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 44(4): 2 (2021) - [c30]Rashidul Islam, Shimei Pan, James R. Foulds:
Can We Obtain Fairness For Free? AIES 2021: 586-596 - [c29]Philip Feldman, Sim Tiwari, Charissa S. L. Cheah, James R. Foulds, Shimei Pan:
Analyzing COVID-19 Tweets with Transformer-based Language Models. ICWSM Workshops 2021 - [c28]Ziqian Zeng, Rashidul Islam, Kamrun Naher Keya, James R. Foulds, Yangqiu Song, Shimei Pan:
Fair Representation Learning for Heterogeneous Information Networks. ICWSM 2021: 877-887 - [c27]Kamrun Naher Keya, Rashidul Islam, Shimei Pan, Ian Stockwell, James R. Foulds:
Equitable Allocation of Healthcare Resources with Fair Survival Models. SDM 2021: 190-198 - [c26]Rashidul Islam, Kamrun Naher Keya, Ziqian Zeng, Shimei Pan, James R. Foulds:
Debiasing Career Recommendations with Neural Fair Collaborative Filtering. WWW 2021: 3779-3790 - [i17]Ziqian Zeng, Rashidul Islam, Kamrun Naher Keya, James R. Foulds, Yangqiu Song, Shimei Pan:
Fair Representation Learning for Heterogeneous Information Networks. CoRR abs/2104.08769 (2021) - [i16]Philip Feldman, Sim Tiwari, Charissa S. L. Cheah, James R. Foulds, Shimei Pan:
Analyzing COVID-19 Tweets with Transformer-based Language Models. CoRR abs/2104.10259 (2021) - [i15]Fatema Hasan, Kevin S. Xu, James R. Foulds, Shimei Pan:
Learning User Embeddings from Temporal Social Media Data: A Survey. CoRR abs/2105.07996 (2021) - [i14]Clarice Wang, Kathryn Wang, Andrew Bian, Rashidul Islam, Kamrun Naher Keya, James R. Foulds, Shimei Pan:
Bias: Friend or Foe? User Acceptance of Gender Stereotypes in Automated Career Recommendations. CoRR abs/2106.07112 (2021) - 2020
- [j6]James R. Foulds, Shimei Pan:
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 43(4): 2 (2020) - [j5]James R. Foulds, Shimei Pan:
Are Parity-Based Notions of AI Fairness Desirable? IEEE Data Eng. Bull. 43(4): 51-73 (2020) - [j4]Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling:
Variational Bayes In Private Settings (VIPS). J. Artif. Intell. Res. 68: 109-157 (2020) - [c25]James R. Foulds, Rashidul Islam, Kamrun Naher Keya, Shimei Pan:
An Intersectional Definition of Fairness. ICDE 2020: 1918-1921 - [c24]James R. Foulds, Mijung Park, Kamalika Chaudhuri, Max Welling:
Variational Bayes in Private Settings (VIPS) (Extended Abstract). IJCAI 2020: 5050-5054 - [c23]James R. Foulds, Rashidul Islam, Kamrun Naher Keya, Shimei Pan:
Bayesian Modeling of Intersectional Fairness: The Variance of Bias. SDM 2020: 424-432 - [c22]Ketki V. Deshpande, Shimei Pan, James R. Foulds:
Mitigating Demographic Bias in AI-based Resume Filtering. UMAP (Adjunct Publication) 2020: 268-275 - [i13]Rashidul Islam, Kamrun Naher Keya, Ziqian Zeng, Shimei Pan, James R. Foulds:
Neural Fair Collaborative Filtering. CoRR abs/2009.08955 (2020) - [i12]Guohou Shan, James R. Foulds, Shimei Pan:
Causal Feature Selection with Dimension Reduction for Interpretable Text Classification. CoRR abs/2010.04609 (2020) - [i11]Kamrun Naher Keya, Rashidul Islam, Shimei Pan, Ian Stockwell, James R. Foulds:
Equitable Allocation of Healthcare Resources with Fair Cox Models. CoRR abs/2010.06820 (2020)
2010 – 2019
- 2019
- [c21]Nilavra Pathak, James R. Foulds, Nirmalya Roy, Nilanjan Banerjee, Ryan W. Robucci:
A Bayesian Data Analytics Approach to Buildings' Thermal Parameter Estimation. e-Energy 2019: 89-99 - [c20]Rashidul Islam, James R. Foulds:
Scalable Collapsed Inference for High-Dimensional Topic Models. NAACL-HLT (1) 2019: 2836-2845 - [i10]Nilavra Pathak, James R. Foulds, Nirmalya Roy, Nilanjan Banerjee, Ryan W. Robucci:
Estimating Buildings' Parameters over Time Including Prior Knowledge. CoRR abs/1901.07469 (2019) - [i9]Kamrun Naher Keya, Yannis Papanikolaou, James R. Foulds:
Neural Embedding Allocation: Distributed Representations of Topic Models. CoRR abs/1909.04702 (2019) - 2018
- [c19]James R. Foulds:
Mixed Membership Word Embeddings for Computational Social Science. AISTATS 2018: 86-95 - [i8]James R. Foulds, Shimei Pan:
An Intersectional Definition of Fairness. CoRR abs/1807.08362 (2018) - [i7]James R. Foulds, Rashidul Islam, Kamrun Keya, Shimei Pan:
Bayesian Modeling of Intersectional Fairness: The Variance of Bias. CoRR abs/1811.07255 (2018) - 2017
- [j3]Yannis Papanikolaou, James R. Foulds, Timothy N. Rubin, Grigorios Tsoumakas:
Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA. J. Mach. Learn. Res. 18: 62:1-62:58 (2017) - [c18]Mijung Park, James R. Foulds, Kamalika Choudhary, Max Welling:
DP-EM: Differentially Private Expectation Maximization. AISTATS 2017: 896-904 - [i6]James R. Foulds:
Mixed Membership Word Embeddings for Computational Social Science. CoRR abs/1705.07368 (2017) - 2016
- [c17]James R. Foulds, Joseph Geumlek, Max Welling, Kamalika Chaudhuri:
On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis. UAI 2016 - [i5]James R. Foulds, Joseph Geumlek, Max Welling, Kamalika Chaudhuri:
On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis. CoRR abs/1603.07294 (2016) - [i4]Mijung Park, Jimmy Foulds, Kamalika Chaudhuri, Max Welling:
Practical Privacy For Expectation Maximization. CoRR abs/1605.06995 (2016) - [i3]Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling:
Private Topic Modeling. CoRR abs/1609.04120 (2016) - [i2]Mijung Park, James R. Foulds, Kamalika Chaudhuri, Max Welling:
Variational Bayes In Private Settings (VIPS). CoRR abs/1611.00340 (2016) - 2015
- [c16]Arti Ramesh, Shachi H. Kumar, James R. Foulds, Lise Getoor:
Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums. ACL (1) 2015: 74-83 - [c15]Dhanya Sridhar, James R. Foulds, Bert Huang, Lise Getoor, Marilyn A. Walker:
Joint Models of Disagreement and Stance in Online Debate. ACL (1) 2015: 116-125 - [c14]Adam Grycner, Gerhard Weikum, Jay Pujara, James R. Foulds, Lise Getoor:
RELLY: Inferring Hypernym Relationships Between Relational Phrases. EMNLP 2015: 971-981 - [c13]James R. Foulds, Shachi H. Kumar, Lise Getoor:
Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models. ICML 2015: 777-786 - [c12]Xinran He, Theodoros Rekatsinas, James R. Foulds, Lise Getoor, Yan Liu:
HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades. ICML 2015: 871-880 - [c11]Shobeir Fakhraei, James R. Foulds, Madhusudana V. S. Shashanka, Lise Getoor:
Collective Spammer Detection in Evolving Multi-Relational Social Networks. KDD 2015: 1769-1778 - [c10]Pigi Kouki, Shobeir Fakhraei, James R. Foulds, Magdalini Eirinaki, Lise Getoor:
HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems. RecSys 2015: 99-106 - 2014
- [b1]James Richard Foulds:
Latent Variable Modeling for Networks and Text: Algorithms, Models and Evaluation Techniques. University of California, Irvine, USA, 2014 - [c9]James R. Foulds, Padhraic Smyth:
Annealing Paths for the Evaluation of Topic Models. UAI 2014: 220-229 - 2013
- [c8]James R. Foulds, Padhraic Smyth:
Modeling Scientific Impact with Topical Influence Regression. EMNLP 2013: 113-123 - [c7]James R. Foulds, Levi Boyles, Christopher DuBois, Padhraic Smyth, Max Welling:
Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation. KDD 2013: 446-454 - [i1]James R. Foulds, Levi Boyles, Christopher DuBois, Padhraic Smyth, Max Welling:
Stochastic Collapsed Variational Bayesian Inference for Latent Dirichlet Allocation. CoRR abs/1305.2452 (2013) - 2011
- [c6]Christopher DuBois, James R. Foulds, Padhraic Smyth:
Latent Set Models for Two-Mode Network Data. ICWSM 2011 - [c5]James R. Foulds, Padhraic Smyth:
Multi-Instance Mixture Models. SDM 2011: 606-617 - [c4]James R. Foulds, Nicholas Navaroli, Padhraic Smyth, Alexander Ihler:
Revisiting MAP Estimation, Message Passing and Perfect Graphs. AISTATS 2011: 278-286 - [c3]James R. Foulds, Christopher DuBois, Arthur U. Asuncion, Carter T. Butts, Padhraic Smyth:
A Dynamic Relational Infinite Feature Model for Longitudinal Social Networks. AISTATS 2011: 287-295 - 2010
- [j2]James R. Foulds, Eibe Frank:
A review of multi-instance learning assumptions. Knowl. Eng. Rev. 25(1): 1-25 (2010) - [c2]James R. Foulds, Eibe Frank:
Speeding Up and Boosting Diverse Density Learning. Discovery Science 2010: 102-116
2000 – 2009
- 2008
- [c1]James R. Foulds, Eibe Frank:
Revisiting Multiple-Instance Learning Via Embedded Instance Selection. Australasian Conference on Artificial Intelligence 2008: 300-310 - 2006
- [j1]James R. Foulds, Les R. Foulds:
Bridge Lane Direction Specification for Sustainable Traffic Management. Asia Pac. J. Oper. Res. 23(2): 141-154 (2006)
Coauthor Index
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