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ORCIDJames R. Foulds
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2020 – today
- 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 T. 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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