Stephen Bach

Assistant Professor
Computer Science Department
Brown University, Providence, RI
sbach@cs.brown.edu
CIT 335

Home | BATS | Projects | Publications | Teaching | CV


Pre-prints
Language Models in the Loop: Incorporating Prompting into Weak Supervision
Ryan Smith, Jason A. Fries, Braden Hancock, and Stephen H. Bach
ArXiv 2205.02318
[bibtex]
@article{smith:arxiv22,
  Author = {Ryan Smith and Jason A. Fries and Braden Hancock and Stephen H. Bach},
  Title = {Language Models in the Loop: {I}ncorporating Prompting into Weak Supervision},
  Volume = {arXiv:2205.02318 [cs.LG]},
  Year = {2022}}
Learning to Compose Soft Prompts for Compositional Zero-Shot Learning
Nihal V. Nayak*, Peilin Yu*, and Stephen H. Bach
ArXiv 2204.03574
[bibtex]
@article{nayak:arxiv22,
  Author = {Nihal V. Nayak and Peilin Yu and Stephen H. Bach},
  Title = {Learning to Compose Soft Prompts for Compositional Zero-Shot Learning},
  Volume = {arXiv:2204.03574 [cs.LG]},
  Year = {2022}}
Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks
Reza Esfandiarpoor, Amy Pu, Mohsen Hajabdollahi, and Stephen H. Bach
ArXiv 2012.07176
[bibtex]
@article{esfandiarpoor:arxiv20,
  Author = {Reza Esfandiarpoor and Amy Pu and Mohsen Hajabdollahi and Stephen H. Bach},
  Title = {Extended Few-Shot Learning: {E}xploiting Existing Resources for Novel Tasks},
  Volume = {arXiv:2012.07176 [cs.LG]},
  Year = {2020}}
2022
Multitask Prompted Training Enables Zero-Shot Task Generalization
Victor Sanh*, Albert Webson*, Colin Raffel*, Stephen H. Bach*, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Fevry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, and Alexander M. Rush
International Conference on Learning Representations (ICLR) 2022
Spotlight Presentation
[bibtex] [code] [project]
@inproceedings{sanh:iclr22,
  Author = {Victor Sanh and Albert Webson and Colin Raffel and Stephen H. Bach and Lintang Sutawika and Zaid Alyafeai and Antoine Chaffin and Arnaud Stiegler and Teven Le Scao and Arun Raja and Manan Dey and M Saiful Bari and Canwen Xu and Urmish Thakker and Shanya Sharma Sharma and Eliza Szczechla and Taewoon Kim and Gunjan Chhablani and Nihal Nayak and Debajyoti Datta and Jonathan Chang and Mike Tian-Jian Jiang and Han Wang and Matteo Manica and Sheng Shen and Zheng Xin Yong and Harshit Pandey and Rachel Bawden and Thomas Wang and Trishala Neeraj and Jos Rozen and Abheesht Sharma and Andrea Santilli and Thibault Fevry and Jason Alan Fries and Ryan Teehan and Stella Biderman and Leo Gao and Tali Bers and Thomas Wolf and Alexander M. Rush},
  Title = {Multitask Prompted Training Enables Zero-Shot Task Generalization},
  Booktitle= {International Conference on Learning Representations (ICLR)},
  Year = {2022}}
Learning from Multiple Noisy Partial Labelers
Peilin Yu, Tiffany Ding, and Stephen H. Bach
Artificial Intelligence and Statistics (AISTATS) 2022
[bibtex]
@inproceedings{yu:aistats22,
  Author = {Peilin Yu and Tiffany Ding and Stephen H. Bach},
  Title = {Learning from Multiple Noisy Partial Labelers},
  Booktitle = {Artificial Intelligence and Statistics (AISTATS)},
  Year = {2022}}
TAGLETS: A System for Automatic Semi-Supervised Learning with Auxiliary Data
Wasu Piriyakulkij, Cristina Menghini, Ross Briden, Nihal V. Nayak, Jeffrey Zhu, Elaheh Raisi, and Stephen H. Bach
Conference on Machine Learning and Systems (MLSys) 2022
[bibtex] [project]
@inproceedings{piriyakulkij:mlsys22,
  Author = {Wasu Piriyakulkij and Cristina Menghini and Ross Briden and Nihal V. Nayak and Jeffrey Zhu and Elaheh Raisi and Stephen H. Bach},
  Title = {{TAGLETS}: {A} System for Automatic Semi-Supervised Learning with Auxiliary Data},
  Booktitle = {Conference on Machine Learning and Systems (MLSys)},
  Year = {2022}}
  
PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts
Stephen H. Bach*, Victor Sanh*, Zheng-Xin Yong, Albert Webson, Colin Raffel, Nihal V. Nayak, Abheesht Sharma, Taewoon Kim, M Saiful Bari, Thibault Fevry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Alan Fries, Maged S. Al-shaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Dragomir Radev, Mike Tian-Jian Jiang, Alexander M. Rush
ACL 2022 Demo
[bibtex] [project]
@inproceedings{bach:acldemo22,
  Author = {Stephen H. Bach and Victor Sanh and Zheng-Xin Yong and Albert Webson and Colin Raffel and Nihal V. Nayak and Abheesht Sharma and Taewoon Kim and M Saiful Bari and Thibault Fevry and Zaid Alyafeai and Manan Dey and Andrea Santilli and Zhiqing Sun and Srulik Ben-David and Canwen Xu and Gunjan Chhablani and Han Wang and Jason Alan Fries and Maged S. Al-shaibani and Shanya Sharma and Urmish Thakker and Khalid Almubarak and Xiangru Tang and Dragomir Radev and Mike Tian-Jian Jiang and Alexander M. Rush},
  Title = {{P}rompt{S}ource: {A}n Integrated Development Environment and Repository for Natural Language Prompts},
  Booktitle= {Meeting of the Association for Computational Linguistics (ACL) Demonstration},
  Year = {2022}}
  
Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations
Jessica Dai, Sohini Upadhyay, Ulrich Aivodji, Stephen H. Bach, and Hima Lakkaraju
AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) 2022
[bibtex]
@inproceedings{dai:aies22,
  Author = {Jessica Dai and Sohini Upadhyay and Ulrich Aivodji and Stephen H. Bach and Hima Lakkaraju},
  Title = {Fairness via Explanation Quality: {E}valuating Disparities in the Quality of Post hoc Explanations},
  Booktitle = {AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES)},
  Year = {2022}}
Zero-Shot Learning with Common Sense Knowledge Graphs
Nihal V. Nayak and Stephen H. Bach
Transactions on Machine Learning Research (TMLR) 2022
[bibtex] [code] [project]
@article{nayak:tmlr22,
  Author = {Nihal V. Nayak and Stephen H. Bach},
  Title = {Zero-Shot Learning with Common Sense Knowledge Graphs},
  Journal = {Transactions on Machine Learning Research (TMLR)},
  Year = {2022}}
BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing
Jason Alan Fries*, Leon Weber*, Natasha Seelam*, Gabriel Altay*, Debajyoti Datta, Samuele Garda, Myungsun Kang, Ruisi Su, Wojciech Kusa, Samuel Cahyawijaya, Fabio Barth, Simon Ott, Matthias Samwald, Stephen H. Bach, Stella Biderman, Mario Sänger, Bo Wang, Alison Callahan, Daniel León Periñán, Théo Gigant, Patrick Haller, Jenny Chim, Jose David Posada, John Michael Giorgi, Karthik Rangasai Sivaraman, Marc Pàmies, Marianna Nezhurina, Robert Martin, Michael Cullan, Moritz Freidank, Nathan Dahlberg, Shubhanshu Mishra, Shamik Bose, Nicholas Michio Broad, Yanis Labrak, Shlok S Deshmukh, Sid Kiblawi, Ayush Singh, Minh Chien Vu, Trishala Neeraj, Jonas Golde, Albert Villanova del Moral, and Benjamin Beilharz
Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track 2022
[bibtex] [project]
@inproceedings{fries:neurips22-db,
  Author = {Jason Alan Fries and Leon Weber and Natasha Seelam and Gabriel Altay and Debajyoti Datta and Samuele Garda and Myungsun Kang and Ruisi Su and Wojciech Kusa and Samuel Cahyawijaya and Fabio Barth and Simon Ott and Matthias Samwald and Stephen H. Bach and Stella Biderman and Mario S{\"a}nger and Bo Wang and Alison Callahan and Daniel Le{\'o}n Peri{\~n}{\'a}n and Th{\'e}o Gigant and Patrick Haller and Jenny Chim and Jose David Posada and John Michael Giorgi and Karthik Rangasai Sivaraman and Marc P{\`a}mies and Marianna Nezhurina and Robert Martin and Michael Cullan and Moritz Freidank and Nathan Dahlberg and Shubhanshu Mishra and Shamik Bose and Nicholas Michio Broad and Yanis Labrak and Shlok S Deshmukh and Sid Kiblawi and Ayush Singh and Minh Chien Vu and Trishala Neeraj and Jonas Golde and Albert Villanova del Moral and Benjamin Beilharz},
  Title = {{BigBIO}: {A} Framework for Data-Centric Biomedical Natural Language Processing},
  Booktitle = {Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track},
  Year = {2022}}
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes
Alessio Mazzetto*, Cristina Menghini*, Andrew Yuan, Eli Upfal, and Stephen H. Bach
Neural Information Processing Systems (NeurIPS) 2022
[bibtex]
@inproceedings{mazzetto:neurips22,
  Author = {Alessio Mazzetto and Cristina Menghini and Andrew Yuan and Eli Upfal and Stephen H. Bach},
  Title = {Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes},
  Booktitle = {Neural Information Processing Systems (NeurIPS)},
  Year = {2022}}
2021
Adversarial Multiclass Learning under Weak Supervision with Performance Guarantees
Alessio Mazzetto*, Cyrus Cousins*, Dylan Sam, Stephen H. Bach, and Eli Upfal
International Conference on Machine Learning (ICML) 2021
[bibtex] [code]
@inproceedings{mazzetto:icml21,
  Author = {Alessio Mazzetto and Cyrus Cousins and Dylan Sam and Stephen H. Bach and Eli Upfal},
  Title = {Adversarial Multiclass Learning under Weak Supervision with Performance Guarantees},
  Booktitle = {International Conference on Machine Learning (ICML)},
  Year = {2021}}
Semi-Supervised Aggregation of Dependent Weak Supervision Sources with Performance Guarantees
Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, and Stephen H. Bach
Artificial Intelligence and Statistics (AISTATS) 2021
[bibtex] [code]
@inproceedings{mazzetto:aistats21,
  Author = {Alessio Mazzetto and Dylan Sam and Andrew Park and Eli Upfal and Stephen H. Bach},
  Title = {Semi-Supervised Aggregation of Dependent Weak Supervision Sources With Performance Guarantees},
  Booktitle = {Artificial Intelligence and Statistics (AISTATS)},
  Year = {2021}}
What will it take to generate fairness-preserving explanations?
Jessica Dai, Sohini Upadhyay, Stephen H. Bach, and Himabindu Lakkaraju
ICML Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI 2021
[bibtex]
@inproceedings{dai:icmlws21,
  Author = {Jessica Dai and Sohini Upadhyay and Stephen H. Bach and Hima Lakkaraju}
  Title = {What will it take to generate fairness-preserving explanations?},
  Booktitle = {ICML Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI},
  Year = {2021}}
2020
Weakly Supervised Sequence Tagging from Noisy Rules
Esteban Safranchik, Shiying Luo, and Stephen H. Bach
AAAI Conference on Artificial Intelligence (AAAI) 2020
[bibtex] [code] [project]
@inproceedings{safranchik:aaai20,
  Author = {Esteban Safranchik and Shiying Luo and Stephen H. Bach},
  Booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  Title = {Weakly Supervised Sequence Tagging from Noisy Rules},
  Year = {2020}}
Snorkel: Rapid Training Data Creation with Weak Supervision
Alexander Ratner, Stephen H. Bach, Henry Ehrenberg, Jason Fries, Sen Wu, and Christopher Ré
The VLDB Journal, 29(2):709-730 2020
[bibtex] [project]
@article{ratner:vldbj20,
  Author = {Alexander J. Ratner and Stephen H. Bach and Henry Ehrenberg and Jason Fries and Sen Wu and Christopher R{\'e}},
  Journal = {The VLDB Journal},
  Number = {2},
  Pages = {709--730},
  Title = {Snorkel: {R}apid Training Data Creation with Weak Supervision},
  Volume = {29},
  Year = {2020}}
Selecting Auxiliary Data Using Knowledge Graphs for Image Classification with Limited Labels
Elaheh Raisi and Stephen H. Bach
CVPR Workshop on Visual Learning with Limited Labels 2020
[bibtex]
@inproceedings{raisi:vl3ws20,
  Author = {Elaheh Raisi and Stephen H. Bach},
  Booktitle = {CVPR Workshop on Visual Learning with Limited Labels},
  Title = {Selecting Auxiliary Data Using Knowledge Graphs for Image Classification with Limited Labels},
  Year = {2020}}
2019
Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale
Stephen H. Bach, Daniel Rodriguez, Yintao Liu, Chong Luo, Haidong Shao, Cassandra Xia, Souvik Sen,
Alexander Ratner, Braden Hancock, Houman Alborzi, Rahul Kuchhal, Christopher Ré, and Rob Malkin
ACM SIGMOD Conference on Management of Data (SIGMOD) Industry Track 2019
[bibtex] [blog] [slides] [poster]
@inproceedings{bach:sigmod19-industrial,
  Author = {Bach, Stephen H. and Rodriguez, Daniel and Liu, Yintao and Luo, Chong and Shao, Haidong and Xia, Cassandra and Sen, Souvik
    and Ratner, Alexander and Hancock, Braden and Alborzi, Houman and Kuchhal, Rahul and R{\'e}, Christopher and Malkin, Rob},
  Booktitle = {ACM SIGMOD Conference on Management of Data (SIGMOD) Industry Track},
  Title = {Snorkel {DryBell}: {A} Case Study in Deploying Weak Supervision at Industrial Scale},
  Year = {2019}}
Learning Visually Grounded Meaning Representations with Sketches
Roma Patel, Stephen H. Bach, and Ellie Pavlick
ICML Workshop on New Tasks for Vision and Language (How2) 2019
[bibtex]
@InProceedings{patel:how219,
  author = "Patel, Roma and Bach, Stephen H. and Pavlick, Ellie",
  title = "Learning Visually Grounded Meaning Representations with Sketches",
  booktitle = "{ICML Workshop on New Tasks for Vision and Language (How2)}",
  year = 2019}
2018
Snorkel: Rapid Training Data Creation with Weak Supervision
Alexander Ratner, Stephen H. Bach, Henry Ehrenberg, Jason Fries, Sen Wu, and Christopher Ré
Proceedings of the VLDB Endowment, 11(3):269-282 2017
Best of VLDB 2018
[bibtex] [project]
@article{ratner:vldb17
  Author = {Ratner, Alexander J. and Bach, Stephen H. and Ehrenberg, Henry E. and R{\'e}, Christopher,},
  Journal = {Proceedings of the VLDB Endowment},
  Title = {Snorkel: {R}apid Training Data Creation with Weak Supervision},
  Volume = {11},
  Number = {3},
  Pages = {269--282},
  Year = {2017}}
2017
Hinge-Loss Markov Random Fields and Probabilistic Soft Logic
Stephen H. Bach, Matthias Broecheler, Bert Huang, and Lise Getoor
Journal of Machine Learning Research, 18(109):1-67 2017
[bibtex] [code]
@article{bach:jmlr17,
  Author = {Bach, Stephen H. and Broecheler, Matthias and Huang, Bert and Getoor, Lise},
  Journal = {Journal of Machine Learning Research (JMLR)},
  Title = {Hinge-Loss {M}arkov Random Fields and Probabilistic Soft Logic},
  Volume = {18},
  Number = {109},
  Pages = {1--67},
  Year = {2017}}
Learning the Structure of Generative Models without Labeled Data
Stephen H. Bach, Bryan He, Alexander Ratner, and Christopher Ré
International Conference on Machine Learning (ICML) 2017
[bibtex] [blog] [talk] [slides] [poster]
@inproceedings{bach:icml17,
  Author = {Bach, Stephen H. and He, Bryan and Ratner, Alexander and R\'e, Christopher},
  Booktitle = {International Conference on Machine Learning (ICML)},
  Title = {Learning the Structure of Generative Models without Labeled Data},
  Year = {2017}}
Soft Quantification in Statistical Relational Learning
Golnoosh Farnadi, Stephen H. Bach, Marie-Francine Moens, Lise Getoor, and Martine De Cock
Machine Learning 2017
[bibtex]
@article{farnadi:ml17,
  Author = {Farnadi, Golnoosh and Bach, Stephen H. and Moens, Marie-Francine and Getoor, Lise and De Cock, Martine},
  Journal = {Machine Learning},
  Title = {Soft Quantification in Statistical Relational Learning},
  Year = {2017}}
Snorkel: Fast Training Set Generation for Information Extraction
Alexander J. Ratner, Stephen H. Bach, Henry R. Ehrenberg, and Christopher Ré
SIGMOD 2017 Demo
[bibtex]
@article{ratner:sigmoddemo17,
  Author = Ratner, Alexander J. and Bach, Stephen H. and Ehrenberg, Henry E. and R{\'e}, Christopher,
  Title = Snorkel: {F}ast Training Set Generation for Information Extraction,
  Volume = {ACM SIGMOD Conference on Management of Data (SIGMOD) Demonstration},
  Year = {2017}}
2016
Interpretable Decision Sets: A Joint Framework for Description and Prediction
Himabindu Lakkaraju, Stephen H. Bach, and Jure Leskovec
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2016
[bibtex] [code]
@inproceedings{lakkaraju:kdd16,
  Author = {Lakkaraju, Himabindu and Bach, Stephen H. and Leskovec, Jure},
  Title = {Interpretable Decision Sets: {A} Joint Framework for Description and Prediction},
  Booktitle = {ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)},
  Year = {2016}}
2015
Hinge-Loss Markov Random Fields and Probabilistic Soft Logic: A Scalable Approach to Structured Prediction
Ph.D. Dissertation, University of Maryland
Larry S. Davis Doctoral Dissertation Award
[bibtex]
@phdthesis{bach:thesis15,
  title    = {Hinge-Loss {M}arkov Random Fields and Probabilistic Soft Logic: {A} Scalable Approach to Structured Prediction},
  school   = {University of Maryland, College Park},
  author   = {Bach, Stephen H.},
  year     = {2015}}
Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs
Stephen H. Bach*, Bert Huang*, Jordan Boyd-Graber, and Lise Getoor
International Conference on Machine Learning (ICML) 2015
[bibtex] [slides] [supplementary] [poster]
@inproceedings{bach:icml15,
  author       = "Bach, Stephen H. and Huang, Bert and Boyd-Graber, Jordan and Getoor, Lise",
  title        = "Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs",
  booktitle    = "International Conference on Machine Learning (ICML)",
  year         = "2015"}
Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees
Stephen H. Bach, Bert Huang, and Lise Getoor
Artificial Intelligence and Statistics (AISTATS) 2015
Selected for oral presentation, 6% of submitted papers (27/442)
[bibtex] [slides] [supplementary] [code]
@inproceedings{bach:aistats15,
  author       = "Bach, Stephen H. and Huang, Bert and Getoor, Lise",
  title        = "Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees",
  booktitle    = "Artificial Intelligence and Statistics (AISTATS)",
  year         = "2015"}
Statistical Relational Learning with Soft Quantifiers
Golnoosh Farnadi, Stephen H. Bach, Marjon Blondeel, Marie-Francine Moens, Lise Getoor, Martine De Cock
International Conference on Inductive Logic Programming (ILP) 2015
Best Student Paper Award
[bibtex]
@InProceedings{farnadi:ilp15,
  author       = "Farnadi, Golnoosh and Bach, Stephen H. and Blondeel, Marjon and Moens, Marie-Francine and Getoor, Lise and De Cock, Martine",
  title        = "Statistical Relational Learning with Soft Quantifiers",
  booktitle    = "International Conference on Inductive Logic Programming (ILP)",
  year         = "2015"}
2014
Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies
Stephen H. Bach, Bert Huang, and Lise Getoor
NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML) 2014
[bibtex] [poster]
@inproceedings{bach:discml14,
  author       = "Bach, Stephen H. and Huang, Bert and Getoor, Lise",
  title        = "Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies",
  booktitle    = "NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML)",
  year         = "2014"}
Probabilistic Soft Logic for Social Good
Stephen H. Bach, Bert Huang, and Lise Getoor
KDD Workshop on Data Science for Social Good 2014
[bibtex] [poster]
@InProceedings{bach:dssg14,
  author       = "Bach, Stephen H. and Huang, Bert and Getoor, Lise",
  title        = "Probabilistic Soft Logic for Social Good",
  booktitle    = "KDD Workshop on Data Science for Social Good",
  year         = "2014"}
Extending PSL with Fuzzy Quantifiers
Golnoosh Farnadi, Stephen H. Bach, Marie-Francine Moens, Lise Getoor, and Martine De Cock
International Workshop on Statistical Relational Artificial Intelligence (StaRAI) 2014
[bibtex]
@InProceedings{farnadi:starai14,
  author       = "Farnadi, Golnoosh and Bach, Stephen H. and Moens, Marie-Francine and Getoor, Lise and De Cock, Martine",
  title        = "Extending PSL with Fuzzy Quantifiers",
  booktitle    = "International Workshop on Statistical Relational Artificial Intelligence (StaRAI)",
  year         = "2014"}
2013
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction
Stephen H. Bach, Bert Huang, Ben London, and Lise Getoor
Uncertainty in Artificial Intelligence (UAI) 2013
[bibtex] [poster] [code]
@inproceedings{bach:uai13,
  author = "Bach, Stephen H. and Huang, Bert and London, Ben and Getoor, Lise",
  title = "Hinge-loss {M}arkov Random Fields: {C}onvex Inference for Structured Prediction",
  booktitle = "{Uncertainty in Artificial Intelligence (UAI)}",
  year = 2013}
Large-Margin Structured Learning for Link Ranking
Stephen H. Bach, Bert Huang, and Lise Getoor
NIPS Workshop on Frontiers of Network Analysis: Methods, Models, and Applications 2013
Best Student Paper Award
[bibtex] [poster] [code]
@inproceedings{bach:fna13,
  author       = "Bach, Stephen H. and Huang, Bert and Getoor, Lise",
  title        = "Large-Margin Structured Learning for Link Ranking",
  booktitle    = "NIPS Workshop on Frontiers of Network Analysis: Methods, Models, and Applications",
  year         = "2013"}
Learning Latent Groups with Hinge-loss Markov Random Fields
Stephen H. Bach, Bert Huang, and Lise Getoor
ICML Workshop on Inferning: Interactions between Inference and Learning 2013
[bibtex] [poster]
@InProceedings{bach:inferning13,
  author = "Bach, Stephen H. and Huang, Bert and Getoor, Lise",
  title = "Learning Latent Groups with Hinge-Loss {M}arkov Random Fields",
  booktitle = "{ICML Workshop on Inferning: Interactions between Inference and Learning}",
  year = 2013}
Collective Activity Detection using Hinge-Loss Markov Random Fields
Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, and Larry Davis
CVPR Workshop on Structured Prediction: Tractability, Learning and Inference 2013
[bibtex]
@InProceedings{london:sptli13,
  author = "London, Ben and Khamis, Sameh and Bach, Stephen H. and Huang, Bert and Getoor, Lise and Davis, Larry",
  title = "Collective Activity Detection using Hinge-loss {M}arkov Random Fields",
  booktitle = "{CVPR Workshop on Structured Prediction: Tractability, Learning and Inference}",
  year = 2013}
2012
Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization
Stephen H. Bach, Matthias Broecheler, Lise Getoor, and Dianne P. O’Leary
Advances in Neural Information Processing Systems (NIPS) 2012
[bibtex] [supplementary] [poster] [code]
@inproceedings{bach:nips12,
  author = "Bach, Stephen H. and Broecheler, Matthias and Getoor, Lise and O'Leary, Dianne P.",
  title = "Scaling {MPE} Inference for Constrained Continuous {M}arkov Random Fields",
  booktitle = "{Advances in Neural Information Processing Systems (NIPS)}",
  year = 2012}
A Short Introduction to Probabilistic Soft Logic
Angelika Kimmig, Stephen H. Bach, Matthias Broecheler, Bert Huang, and Lise Getoor
NIPS Workshop on Probabilistic Programming: Foundations and Applications 2012
[bibtex]
@inproceedings{kimmig:probprog12,
  author = "Kimmig, Angelika and Bach, Stephen H. and Broecheler, Matthias and Huang, Bert and Getoor, Lise",
  title = "A Short Introduction to Probabilistic Soft Logic",
  booktitle = "{NIPS Workshop on Probabilistic Programming: Foundations and Applications}",
  year = 2012}
Social Group Modeling with Probabilistic Soft Logic
Bert Huang, Stephen H. Bach, Eric Norris, Jay Pujara, and Lise Getoor
NIPS Workshop on Social Network and Social Media Analysis: Methods, Models, and Applications 2012
[bibtex]
@inproceedings{huang:snsma12,
  author = "Huang, Bert and Bach, Stephen H. and Norris, Eric and Pujara, Jay and Getoor, Lise",
  title = "Social Group Modeling with Probabilistic Soft Logic",
  booktitle = "{NIPS Workshop on Social Network and Social Media Analysis: Methods, Models, and Applications}",
  year = 2012}
Graph Summarization in Annotated Data Using Probabilistic Soft Logic
Alex Memory, Angelika Kimmig, Stephen H. Bach, Louiqa Raschid, and Lise Getoor
International Workshop on Uncertainty Reasoning for the Semantic Web (URSW) 2012
[bibtex]
@inproceedings{memory:ursw12,
  author = "Memory, Alex and Kimmig, Angelika and Bach, Stephen H. and Raschid, Louiqa and Getoor, Lise",
  title = "Graph Summarization in Annotated Data Using Probabilistic Soft Logic",
  booktitle = "{International Workshop on Uncertainty Reasoning for the Semantic Web (URSW)}",
  year = 2012}
Older
A Bayesian Approach to Concept Drift
Stephen H. Bach and Marcus A. Maloof
Advances in Neural Information Processing Systems (NIPS) 2010
[bibtex] [poster]
@inproceedings{bach:nips10,
  author = "Bach, Stephen H. and Maloof, Marcus A.",
  title = "A {B}ayesian Approach to Concept Drift",
  booktitle = "{Advances in Neural Information Processing Systems (NIPS)}",
  year = 2010}
Decision-Driven Models with Probabilistic Soft Logic
Stephen H. Bach, Matthias Broecheler, Stanley Kok, and Lise Getoor
NIPS Workshop on Predictive Models in Personalized Medicine 2010
[bibtex] [poster]
@InProceedings{bach:pmpm10,
  author = "Bach, Stephen H. and Broecheler, Matthias and Kok, Stanley and Getoor, Lise",
  title = "Decision-Driven Models with Probabilistic Soft Logic",
  booktitle = "{NIPS Workshop on Predictive Models in Personalized Medicine}",
  year = 2010}
Paired Learners for Concept Drift
Stephen H. Bach* and Marcus A. Maloof*
IEEE International Conference on Data Mining (ICDM) 2008
[bibtex]
@inproceedings{bach:icdm08,
  author = "Bach, Stephen H. and Maloof, Marcus A.",
  title = "Paired Learners for Concept Drift",
  booktitle = "{IEEE International Conference on Data Mining (ICDM)}",
  year = 2008}


( * Equal Contributors)