Charles Sutton

167 papers A* 35A 10B 4Journal 82Unranked 35

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Natural Language Outlines for Code: Literate Programming in the LLM Era. SIGSOFT FSE Companion Kensen Shi, Deniz Altinbüken, Saswat Anand, Mihai Christodorescu, Katja Grünwedel, Alexa Koenings, Sai Naidu, Anurag Pathak, Marc Rasi, Fredde Ribeiro, Brandon Ruffin, Siddhant Sanyam, Maxim Tabachnyk, Sara Toth, Roy Tu, Tobias Welp, Pengcheng Yin, Manzil Zaheer, Satish Chandra, Charles Sutton
2024	A*	`conf`	A Probabilistic Framework for Modular Continual Learning. ICLR Lazar Valkov, Akash Srivastava, Swarat Chaudhuri, Charles Sutton
2024	A*	`conf`	ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis. ICLR Kensen Shi, Joey Hong, Yinlin Deng, Pengcheng Yin, Manzil Zaheer, Charles Sutton
2024	A*	`conf`	NExT: Teaching Large Language Models to Reason about Code Execution. ICML Ansong Ni, Miltiadis Allamanis, Arman Cohan, Yinlin Deng, Kensen Shi, Charles Sutton, Pengcheng Yin
2024	J	`jnl`	NExT: Teaching Large Language Models to Reason about Code Execution. CoRR Ansong Ni, Miltiadis Allamanis, Arman Cohan, Yinlin Deng, Kensen Shi, Charles Sutton, Pengcheng Yin
2024	J	`jnl`	Natural Language Outlines for Code: Literate Programming in the LLM Era. CoRR Kensen Shi, Deniz Altinbüken, Saswat Anand, Mihai Christodorescu, Katja Grünwedel, Alexa Koenings, Sai Naidu, Anurag Pathak, Marc Rasi, Fredde Ribeiro, Brandon Ruffin, Siddhant Sanyam, Maxim Tabachnyk, Sara Toth, Roy Tu, Tobias Welp, Pengcheng Yin, Manzil Zaheer, Satish Chandra, Charles Sutton
2024	A*	`conf`	UQE: A Query Engine for Unstructured Databases. NeurIPS Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans
2024	J	`jnl`	UQE: A Query Engine for Unstructured Databases. CoRR Hanjun Dai, Bethany Wang, Xingchen Wan, Bo Dai, Sherry Yang, Azade Nova, Pengcheng Yin, Phitchaya Mangpo Phothilimthana, Charles Sutton, Dale Schuurmans
2023	J	`jnl`	A Probabilistic Framework for Modular Continual Learning. CoRR Lazar Valkov, Akash Srivastava, Swarat Chaudhuri, Charles Sutton
2023	A*	`conf`	Any-scale Balanced Samplers for Discrete Space. ICLR Haoran Sun, Bo Dai, Charles Sutton, Dale Schuurmans, Hanjun Dai
2023	A*	`conf`	Can Large Language Models Reason about Program Invariants? ICML Kexin Pei, David Bieber, Kensen Shi, Charles Sutton, Pengcheng Yin
2023	J	`jnl`	ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis. CoRR Kensen Shi, Joey Hong, Manzil Zaheer, Pengcheng Yin, Charles Sutton
2023	A*	`conf`	LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. NeurIPS Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
2023	J	`jnl`	LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas. CoRR Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
2023	—	`conf`	Natural Language to Code Generation in Interactive Data Science Notebooks. ACL (1) Pengcheng Yin, Wen-Ding Li, Kefan Xiao, Abhishek Rao, Yeming Wen, Kensen Shi, Joshua Howland, Paige Bailey, Michele Catasta, Henryk Michalewski, Oleksandr Polozov, Charles Sutton
2023	J	`jnl`	PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel
2023	J	`jnl`	Programming Language Processing (Dagstuhl Seminar 23062). Dagstuhl Reports Michael Pradel, Baishakhi Ray, Charles Sutton, Eran Yahav
2023	A*	`conf`	Training Chain-of-Thought via Latent-Variable Inference. NeurIPS Matthew Douglas Hoffman, Du Phan, David Dohan, Sholto Douglas, Tuan Anh Le, Aaron Parisi, Pavel Sountsov, Charles Sutton, Sharad Vikram, Rif A. Saurous
2023	J	`jnl`	Training Chain-of-Thought via Latent-Variable Inference. CoRR Du Phan, Matthew D. Hoffman, David Dohan, Sholto Douglas, Tuan Anh Le, Aaron Parisi, Pavel Sountsov, Charles Sutton, Sharad Vikram, Rif A. Saurous
2023	J	`jnl`	Universal Self-Consistency for Large Language Model Generation. CoRR Xinyun Chen, Renat Aksitov, Uri Alon, Jie Ren, Kefan Xiao, Pengcheng Yin, Sushant Prakash, Charles Sutton, Xuezhi Wang, Denny Zhou
2022	J	`jnl`	A Library for Representing Python Programs as Graphs for Machine Learning. CoRR David Bieber, Kensen Shi, Petros Maniatis, Charles Sutton, Vincent J. Hellendoorn, Daniel D. Johnson, Daniel Tarlow
2022	J	`jnl`	Compositional Generalization and Decomposition in Neural Program Synthesis. CoRR Kensen Shi, Joey Hong, Manzil Zaheer, Pengcheng Yin, Charles Sutton
2022	J	`jnl`	Conditional Independence by Typing. ACM Trans. Program. Lang. Syst. Maria I. Gorinova, Andrew D. Gordon, Charles Sutton, Matthijs Vákár
2022	A*	`conf`	CrossBeam: Learning to Search in Bottom-Up Program Synthesis. ICLR Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton
2022	J	`jnl`	CrossBeam: Learning to Search in Bottom-Up Program Synthesis. CoRR Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton
2022	J	`jnl`	Language Model Cascades. CoRR David Dohan, Winnie Xu, Aitor Lewkowycz, Jacob Austin, David Bieber, Raphael Gontijo Lopes, Yuhuai Wu, Henryk Michalewski, Rif A. Saurous, Jascha Sohl-Dickstein, Kevin Murphy, Charles Sutton
2022	—	`ed.`	MAPS@PLDI 2022: 6th ACM SIGPLAN International Symposium on Machine Programming, San Diego, CA, USA, 13 June 2022 MAPS@PLDI Swarat Chaudhuri, Charles Sutton
2022	J	`jnl`	Natural Language to Code Generation in Interactive Data Science Notebooks. CoRR Pengcheng Yin, Wen-Ding Li, Kefan Xiao, Abhishek Rao, Yeming Wen, Kensen Shi, Joshua Howland, Paige Bailey, Michele Catasta, Henryk Michalewski, Alex Polozov, Charles Sutton
2022	J	`jnl`	PaLM: Scaling Language Modeling with Pathways. CoRR Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel
2022	J	`jnl`	Repairing Systematic Outliers by Learning Clean Subspaces in VAEs. CoRR Simão Eduardo, Kai Xu, Alfredo Nazábal, Charles Sutton
2021	A*	`conf`	A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics. NeurIPS Kai Xu, Akash Srivastava, Dan Gutfreund, Felix Sosa, Tomer D. Ullman, Josh Tenenbaum, Charles Sutton
2021	A*	`conf`	BUSTLE: Bottom-Up Program Synthesis Through Learning-Guided Exploration. ICLR Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton, Hanjun Dai
2021	A	`conf`	Couplings for Multinomial Hamiltonian Monte Carlo. AISTATS Kai Xu, Tor Erlend Fjelde, Charles Sutton, Hong Ge
2021	A*	`conf`	Latent Programmer: Discrete Latent Codes for Program Synthesis. ICML Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer
2021	A*	`conf`	Learning Semantic Representations to Verify Hardware Designs. NeurIPS Shobha Vasudevan, Wenjie Jiang, David Bieber, Rishabh Singh, Hamid Shojaei, Richard Ho, Charles Sutton
2021	J	`jnl`	Program Synthesis with Large Language Models. CoRR Jacob Austin, Augustus Odena, Maxwell I. Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie J. Cai, Michael Terry, Quoc V. Le, Charles Sutton
2021	J	`jnl`	Show Your Work: Scratchpads for Intermediate Computation with Language Models. CoRR Maxwell I. Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, Charles Sutton, Augustus Odena
2021	A*	`conf`	SpreadsheetCoder: Formula Prediction from Semi-structured Context. ICML Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
2021	J	`jnl`	SpreadsheetCoder: Formula Prediction from Semi-structured Context. CoRR Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
2020	J	`jnl`	BUSTLE: Bottom-up program-Synthesis Through Learning-guided Exploration. CoRR Augustus Odena, Kensen Shi, David Bieber, Rishabh Singh, Charles Sutton
2020	J	`jnl`	Big Code != Big Vocabulary: Open-Vocabulary Models for Source Code. CoRR Rafael-Michael Karampatsis, Hlib Babii, Romain Robbes, Charles Sutton, Andrea Janes
2020	A*	`conf`	Big code != big vocabulary: open-vocabulary models for source code. ICSE Rafael-Michael Karampatsis, Hlib Babii, Romain Robbes, Charles Sutton, Andrea Janes
2020	J	`jnl`	Conditional independence by typing. CoRR Maria I. Gorinova, Andrew D. Gordon, Charles Sutton, Matthijs Vákár
2020	A*	`conf`	Generative Ratio Matching Networks. ICLR Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton
2020	A*	`conf`	Global Relational Models of Source Code. ICLR Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, David Bieber
2020	A	`conf`	How Often Do Single-Statement Bugs Occur?: The ManySStuBs4J Dataset. MSR Rafael-Michael Karampatsis, Charles Sutton
2020	A*	`conf`	Incremental Sampling Without Replacement for Sequence Models. ICML Kensen Shi, David Bieber, Charles Sutton
2020	J	`jnl`	Incremental Sampling Without Replacement for Sequence Models. CoRR Kensen Shi, David Bieber, Charles Sutton
2020	J	`jnl`	Latent Programmer: Discrete Latent Codes for Program Synthesis. CoRR Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer
2020	A*	`conf`	Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. NeurIPS Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
2020	J	`jnl`	Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration. CoRR Hanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans
2020	A*	`conf`	Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks. NeurIPS David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow
2020	J	`jnl`	Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks. CoRR David Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow
2020	—	`conf`	Learning to Fix Build Errors with Graph2Diff Neural Networks. ICSE (Workshops) Daniel Tarlow, Subhodeep Moitra, Andrew Rice, Zimin Chen, Pierre-Antoine Manzagol, Charles Sutton, Edward Aftandilian
2020	A*	`conf`	Learning to Represent Programs with Property Signatures. ICLR Augustus Odena, Charles Sutton
2020	J	`jnl`	Learning to Represent Programs with Property Signatures. CoRR Augustus Odena, Charles Sutton
2020	J	`jnl`	Neural Program Synthesis with a Differentiable Fixer. CoRR Matej Balog, Rishabh Singh, Petros Maniatis, Charles Sutton
2020	—	`conf`	Open-vocabulary models for source code. ICSE (Companion Volume) Rafael-Michael Karampatsis, Hlib Babii, Romain Robbes, Charles Sutton, Andrea Janes
2020	J	`jnl`	OptTyper: Probabilistic Type Inference by Optimising Logical and Natural Constraints. CoRR Irene Vlassi Pandi, Earl T. Barr, Andrew D. Gordon, Charles Sutton
2020	A	`conf`	Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data. AISTATS Simão Eduardo, Alfredo Nazábal, Christopher K. I. Williams, Charles Sutton
2020	J	`jnl`	SCELMo: Source Code Embeddings from Language Models. CoRR Rafael-Michael Karampatsis, Charles Sutton
2020	J	`jnl`	Towards Modular Algorithm Induction. CoRR Daniel A. Abolafia, Rishabh Singh, Manzil Zaheer, Charles Sutton
2020	—	`conf`	Where should I comment my code?: a dataset and model for predicting locations that need comments. ICSE (NIER) Annie Louis, Santanu Kumar Dash, Earl T. Barr, Michael D. Ernst, Charles Sutton
2019	A*	`conf`	ColNet: Embedding the Semantics of Web Tables for Column Type Prediction. AAAI Jiaoyan Chen, Ernesto Jiménez-Ruiz, Ian Horrocks, Charles Sutton
2019	B	`conf`	GEMSEC: graph embedding with self clustering. ASONAM Benedek Rozemberczki, Ryan Davies, Rik Sarkar, Charles Sutton
2019	J	`jnl`	How Often Do Single-Statement Bugs Occur? The ManySStuBs4J Dataset. CoRR Rafael-Michael Karampatsis, Charles Sutton
2019	A*	`conf`	Learning Semantic Annotations for Tabular Data. IJCAI Jiaoyan Chen, Ernesto Jiménez-Ruiz, Ian Horrocks, Charles Sutton
2019	J	`jnl`	Learning Semantic Annotations for Tabular Data. CoRR Jiaoyan Chen, Ernesto Jiménez-Ruiz, Ian Horrocks, Charles Sutton
2019	J	`jnl`	Learning to Fix Build Errors with Graph2Diff Neural Networks. CoRR Daniel Tarlow, Subhodeep Moitra, Andrew Rice, Zimin Chen, Pierre-Antoine Manzagol, Charles Sutton, Edward Aftandilian
2019	J	`jnl`	Maybe Deep Neural Networks are the Best Choice for Modeling Source Code. CoRR Rafael-Michael Karampatsis, Charles Sutton
2019	J	`jnl`	Probabilistic programming with densities in SlicStan: efficient, flexible, and deterministic. Proc. ACM Program. Lang. Maria I. Gorinova, Andrew D. Gordon, Charles Sutton
2019	J	`jnl`	Robust Variational Autoencoders for Outlier Detection in Mixed-Type Data. CoRR Simão Eduardo, Alfredo Nazábal, Christopher K. I. Williams, Charles Sutton
2019	A*	`conf`	Variational Russian Roulette for Deep Bayesian Nonparametrics. ICML Kai Xu, Akash Srivastava, Charles Sutton
2019	J	`jnl`	Wrangling messy CSV files by detecting row and type patterns. Data Min. Knowl. Discov. Gerrit J. J. van den Burg, Alfredo Nazábal, Charles Sutton
2018	J	`jnl`	A Survey of Machine Learning for Big Code and Naturalness. ACM Comput. Surv. Miltiadis Allamanis, Earl T. Barr, Premkumar T. Devanbu, Charles Sutton
2018	J	`jnl`	ColNet: Embedding the Semantics of Web Tables for Column Type Prediction. CoRR Jiaoyan Chen, Ernesto Jiménez-Ruiz, Ian Horrocks, Charles Sutton
2018	A*	`conf`	Data Diff: Interpretable, Executable Summaries of Changes in Distributions for Data Wrangling. KDD Charles Sutton, Timothy Hobson, James Geddes, Rich Caruana
2018	—	`conf`	Deep Dungeons and Dragons: Learning Character-Action Interactions from Role-Playing Game Transcripts. NAACL-HLT (2) Annie Louis, Charles Sutton
2018	J	`jnl`	Deep Learning to Detect Redundant Method Comments. CoRR Annie Louis, Santanu Kumar Dash, Earl T. Barr, Charles Sutton
2018	J	`jnl`	GEMSEC: Graph Embedding with Self Clustering. CoRR Benedek Rozemberczki, Ryan Davies, Rik Sarkar, Charles Sutton
2018	A*	`conf`	HOUDINI: Lifelong Learning as Program Synthesis. NeurIPS Lazar Valkov, Dipak Chaudhari, Akash Srivastava, Charles Sutton, Swarat Chaudhuri
2018	J	`jnl`	Interpreting Deep Classifier by Visual Distillation of Dark Knowledge. CoRR Kai Xu, Dae Hoon Park, Chang Yi, Charles Sutton
2018	J	`jnl`	Mining Semantic Loop Idioms. IEEE Trans. Software Eng. Miltiadis Allamanis, Earl T. Barr, Christian Bird, Premkumar T. Devanbu, Mark Marron, Charles Sutton
2018	J	`jnl`	Probabilistic Programming with Densities in SlicStan: Efficient, Flexible and Deterministic. CoRR Maria I. Gorinova, Andrew D. Gordon, Charles Sutton
2018	J	`jnl`	Ratio Matching MMD Nets: Low dimensional projections for effective deep generative models. CoRR Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton
2018	A*	`conf`	Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring. AAAI Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang, Nigel H. Goddard, Charles Sutton
2018	B	`conf`	Summarizing Software API Usage Examples Using Clustering Techniques. FASE Nikolaos Katirtzis, Themistoklis Diamantopoulos, Charles Sutton
2018	J	`jnl`	Synthesis of Differentiable Functional Programs for Lifelong Learning. CoRR Lazar Valkov, Dipak Chaudhari, Akash Srivastava, Charles Sutton, Swarat Chaudhuri
2018	J	`jnl`	Variational Inference In Pachinko Allocation Machines. CoRR Akash Srivastava, Charles Sutton
2018	J	`jnl`	Wrangling Messy CSV Files by Detecting Row and Type Patterns. CoRR Gerrit J. J. van den Burg, Alfredo Nazábal, Charles Sutton
2018	—	`conf`	Wrattler: Reproducible, live and polyglot notebooks. TaPP Tomas Petricek, James Geddes, Charles Sutton
2017	J	`jnl`	A Survey of Machine Learning for Big Code and Naturalness. CoRR Miltiadis Allamanis, Earl T. Barr, Premkumar T. Devanbu, Charles Sutton
2017	—	`conf`	Autoencoding Variational Inference For Topic Models. ICLR (Poster) Akash Srivastava, Charles Sutton
2017	J	`jnl`	Autofolding for Source Code Summarization. IEEE Trans. Software Eng. Jaroslav M. Fowkes, Pankajan Chanthirasegaran, Razvan Ranca, Miltiadis Allamanis, Mirella Lapata, Charles Sutton
2017	A*	`conf`	Learning Continuous Semantic Representations of Symbolic Expressions. ICML Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli, Charles Sutton
2017	J	`jnl`	Popularity of arXiv.org within Computer Science. CoRR Charles Sutton, Linan Gong
2017	—	`conf`	VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning. NIPS Akash Srivastava, Lazar Valkov, Chris Russell, Michael U. Gutmann, Charles Sutton
2016	J	`jnl`	A Bayesian Approach to Parameter Inference in Queueing Networks. ACM Trans. Model. Comput. Simul. Weikun Wang, Giuliano Casale, Charles Sutton
2016	—	`conf`	A Bayesian Network Model for Interesting Itemsets. ECML/PKDD (2) Jaroslav M. Fowkes, Charles Sutton
2016	A*	`conf`	A Convolutional Attention Network for Extreme Summarization of Source Code. ICML Miltiadis Allamanis, Hao Peng, Charles Sutton
2016	J	`jnl`	A Convolutional Attention Network for Extreme Summarization of Source Code. CoRR Miltiadis Allamanis, Hao Peng, Charles Sutton
2016	A*	`conf`	A Subsequence Interleaving Model for Sequential Pattern Mining. KDD Jaroslav M. Fowkes, Charles Sutton
2016	J	`jnl`	A Subsequence Interleaving Model for Sequential Pattern Mining. CoRR Jaroslav M. Fowkes, Charles Sutton
2016	—	`conf`	A text-mining approach to explain unwanted behaviours. EUROSEC Wei Chen, David Aspinall, Andrew D. Gordon, Charles Sutton, Igor Muttik
2016	J	`jnl`	Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation. CoRR Akash Srivastava, James Y. Zou, Ryan P. Adams, Charles Sutton
2016	J	`jnl`	Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation. CoRR Akash Srivastava, James Y. Zou, Ryan P. Adams, Charles Sutton
2016	—	`conf`	Composite Denoising Autoencoders. ECML/PKDD (1) Krzysztof J. Geras, Charles Sutton
2016	—	`conf`	Context Matters: Towards Extracting a Citation's Context Using Linguistic Features. JCDL Daniel Duma, Charles Sutton, Ewan Klein
2016	—	`conf`	Explaining Unwanted Behaviours in Context. IMPS@ESSoS Wei Chen, David Aspinall, Andrew D. Gordon, Charles Sutton, Igor Muttik
2016	J	`jnl`	Learning Continuous Semantic Representations of Symbolic Expressions. CoRR Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli, Charles Sutton
2016	—	`conf`	More Semantics More Robust: Improving Android Malware Classifiers. WISEC Wei Chen, David Aspinall, Andrew D. Gordon, Charles Sutton, Igor Muttik
2016	B	`conf`	On Robust Malware Classifiers by Verifying Unwanted Behaviours. IFM Wei Chen, David Aspinall, Andrew D. Gordon, Charles Sutton, Igor Muttik
2016	—	`conf`	Parameter-free probabilistic API mining across GitHub. SIGSOFT FSE Jaroslav M. Fowkes, Charles Sutton
2016	J	`jnl`	Sequence-to-point learning with neural networks for nonintrusive load monitoring. CoRR Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang, Nigel H. Goddard, Charles Sutton
2016	—	`conf`	TASSAL: autofolding for source code summarization. ICSE (Companion Volume) Jaroslav M. Fowkes, Pankajan Chanthirasegaran, Razvan Ranca, Miltiadis Allamanis, Mirella Lapata, Charles Sutton
2016	J	`jnl`	Tailored Mutants Fit Bugs Better. CoRR Miltiadis Allamanis, Earl T. Barr, René Just, Charles Sutton
2015	J	`jnl`	A Bayesian Network Model for Interesting Itemsets. CoRR Jaroslav M. Fowkes, Charles Sutton
2015	J	`jnl`	Compressing LSTMs into CNNs. CoRR Krzysztof J. Geras, Abdel-rahman Mohamed, Rich Caruana, Gregor Urban, Shengjie Wang, Özlem Aslan, Matthai Philipose, Matthew Richardson, Charles Sutton
2015	—	`conf`	Latent Bayesian melding for integrating individual and population models. NIPS Mingjun Zhong, Nigel H. Goddard, Charles Sutton
2015	J	`jnl`	Latent Bayesian melding for integrating individual and population models. CoRR Mingjun Zhong, Nigel H. Goddard, Charles Sutton
2015	J	`jnl`	Parameter-Free Probabilistic API Mining at GitHub Scale. CoRR Jaroslav M. Fowkes, Charles Sutton
2015	J	`jnl`	Programming with "Big Code" (Dagstuhl Seminar 15472). Dagstuhl Reports William W. Cohen, Charles Sutton, Martin T. Vechev
2015	—	`conf`	Scheduled denoising autoencoders. ICLR (Poster) Krzysztof J. Geras, Charles Sutton
2015	—	`conf`	Suggesting accurate method and class names. ESEC/SIGSOFT FSE Miltiadis Allamanis, Earl T. Barr, Christian Bird, Charles Sutton
2014	J	`jnl`	Autofolding for Source Code Summarization. CoRR Jaroslav M. Fowkes, Razvan Ranca, Miltiadis Allamanis, Mirella Lapata, Charles Sutton
2014	J	`jnl`	Learning Natural Coding Conventions. CoRR Miltiadis Allamanis, Earl T. Barr, Charles Sutton
2014	—	`conf`	Learning natural coding conventions. SIGSOFT FSE Miltiadis Allamanis, Earl T. Barr, Christian Bird, Charles Sutton
2014	J	`jnl`	Mining Idioms from Source Code. CoRR Miltiadis Allamanis, Charles Sutton
2014	—	`conf`	Mining idioms from source code. SIGSOFT FSE Miltiadis Allamanis, Charles Sutton
2014	—	`conf`	Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models. NIPS Yichuan Zhang, Charles Sutton
2014	J	`jnl`	Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models. CoRR Yichuan Zhang, Charles Sutton
2014	—	`conf`	Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation. NIPS Mingjun Zhong, Nigel H. Goddard, Charles Sutton
2014	A*	`conf`	Word storms: multiples of word clouds for visual comparison of documents. WWW Quim Castellà, Charles Sutton
2013	A	`conf`	Mining source code repositories at massive scale using language modeling. MSR Miltiadis Allamanis, Charles Sutton
2013	—	`conf`	Multiple-source cross-validation. ICML (3) Krzysztof J. Geras, Charles Sutton
2013	J	`jnl`	Supporting User-Defined Functions on Uncertain Data. Proc. VLDB Endow. Thanh T. L. Tran, Yanlei Diao, Charles Sutton, Anna Liu
2013	A	`conf`	Why, when, and what: analyzing stack overflow questions by topic, type, and code. MSR Miltiadis Allamanis, Charles Sutton
2013	J	`jnl`	Word Storms: Multiples of Word Clouds for Visual Comparison of Documents CoRR Quim Castellà, Charles Sutton
2012	J	`jnl`	An Introduction to Conditional Random Fields. Found. Trends Mach. Learn. Charles Sutton, Andrew McCallum
2012	—	`conf`	Continuous Relaxations for Discrete Hamiltonian Monte Carlo. NIPS Yichuan Zhang, Charles Sutton, Amos J. Storkey, Zoubin Ghahramani
2012	J	`jnl`	Improved Dynamic Schedules for Belief Propagation CoRR Charles Sutton, Andrew McCallum
2012	—	`conf`	Machine learning and multimedia content generation for energy demand reduction. SustainIT Nigel H. Goddard, Johanna D. Moore, Charles Sutton, Heather Lovell, Janette Webb
2012	J	`jnl`	Piecewise Training for Undirected Models CoRR Charles Sutton, Andrew McCallum
2011	J	`jnl`	Distributed Inference and Query Processing for RFID Tracking and Monitoring CoRR Zhao Cao, Charles Sutton, Yanlei Diao, Prashant J. Shenoy
2011	J	`jnl`	Distributed inference and query processing for RFID tracking and monitoring. Proc. VLDB Endow. Zhao Cao, Charles Sutton, Yanlei Diao, Prashant J. Shenoy
2011	—	`conf`	Quasi-Newton Methods for Markov Chain Monte Carlo. NIPS Yichuan Zhang, Charles Sutton
2010	J	`jnl`	Bayesian Inference in Queueing Networks CoRR Charles Sutton, Michael I. Jordan
2010	A	`conf`	Inference and Learning in Networks of Queues. AISTATS Charles Sutton, Michael I. Jordan
2009	—	`conf`	Automatic exploration of datacenter performance regimes. ACDC@ICAC Peter Bodík, Rean Griffith, Charles Sutton, Armando Fox, Michael I. Jordan, David A. Patterson
2009	J	`jnl`	Capturing Data Uncertainty in High-Volume Stream Processing CoRR Yanlei Diao, Boduo Li, Anna Liu, Liping Peng, Charles Sutton, Thanh T. L. Tran, Michael Zink
2009	A	`conf`	Capturing Data Uncertainty in High-Volume Stream Processing. CIDR Yanlei Diao, Boduo Li, Anna Liu, Liping Peng, Charles Sutton, Thanh T. L. Tran, Michael Zink
2009	J	`jnl`	Piecewise training for structured prediction. Mach. Learn. Charles Sutton, Andrew McCallum
2009	A*	`conf`	Probabilistic Inference over RFID Streams in Mobile Environments. ICDE Thanh T. L. Tran, Charles Sutton, Richard Cocci, Yanming Nie, Yanlei Diao, Prashant J. Shenoy
2009	—	`conf`	Statistical Machine Learning Makes Automatic Control Practical for Internet Datacenters. HotCloud Peter Bodík, Rean Griffith, Charles Sutton, Armando Fox, Michael I. Jordan, David A. Patterson
2008	—	`conf`	Exploiting Machine Learning to Subvert Your Spam Filter. LEET Blaine Nelson, Marco Barreno, Fuching Jack Chi, Anthony D. Joseph, Benjamin I. P. Rubinstein, Udam Saini, Charles Sutton, J. Doug Tygar, Kai Xia
2008	—	`conf`	Probabilistic Inference in Queueing Networks. SysML Charles Sutton, Michael I. Jordan
2008	A*	`conf`	Unsupervised deduplication using cross-field dependencies. KDD Robert J. Hall, Charles Sutton, Andrew McCallum
2007	J	`jnl`	Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data. J. Mach. Learn. Res. Charles Sutton, Andrew McCallum, Khashayar Rohanimanesh
2007	A	`conf`	Improved Dynamic Schedules for Belief Propagation. UAI Charles Sutton, Andrew McCallum
2007	A*	`conf`	Piecewise pseudolikelihood for efficient training of conditional random fields. ICML Charles Sutton, Andrew McCallum
2006	—	`conf`	Reducing Weight Undertraining in Structured Discriminative Learning. HLT-NAACL Charles Sutton, Michael Sindelar, Andrew McCallum
2006	—	`conf`	Sparse Forward-Backward Using Minimum Divergence Beams for Fast Training Of Conditional Random Fields. ICASSP (5) Chris Pal, Charles Sutton, Andrew McCallum
2005	—	`conf`	Composition of Conditional Random Fields for Transfer Learning. HLT/EMNLP Charles Sutton, Andrew McCallum
2005	B	`conf`	Joint Parsing and Semantic Role Labeling. CoNLL Charles Sutton, Andrew McCallum
2005	A	`conf`	Learning in Markov Random Fields with Contrastive Free Energies. AISTATS Max Welling, Charles Sutton
2005	A	`conf`	Piecewise Training for Undirected Models. UAI Charles Sutton, Andrew McCallum
2004	A*	`conf`	Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data. ICML Charles Sutton, Khashayar Rohanimanesh, Andrew McCallum