| 2026 | AAAI | Near-optimal Linear Predictive Clustering in Non-separable Spaces via MIP and QPBO Reductions. | Jiazhou Liang, Hassan Khurram, Scott Sanner |
| 2026 | AAAI | Efficient Modality Translation via Arbitrary Conditioning and Wasserstein Regularization. | Toms Tokr, Scott Sanner |
| 2026 | ACL | Bayesian Active Learning with Gaussian Processes Guided by LLM Relevance Scoring for Dense Passage Retrieval. | Junyoung Kim, Anton Korikov, Jiazhou Liang, Justin Cui, Yifan Simon Liu, Qianfeng Wen, Mark Zhao, Scott Sanner |
| 2026 | ACL | Evaluating Scene-based In-Situ Item Labeling for Immersive Conversational Recommendation. | Jiazhou Liang, Yifan Simon Liu, David Guo, Yilun Jiang, Minqi Sun, Scott Sanner |
| 2026 | ACL | Semantic XPath: Structured Agentic Memory Access for Conversational AI. | Yifan Simon Liu, Ruifan Wu, Liam Gallagher, Jiazhou Liang, Armin Toroghi, Scott Sanner |
| 2026 | ACL | Multimodal Item Scoring for Natural Language Recommendation via Gaussian Process Regression with LLM Relevance Judgments. | Yifan Simon Liu, Qianfeng Wen, Jiazhou Liang, Mark Zhao, Justin Cui, Anton Korikov, Armin Toroghi, Junyoung Kim, Scott Sanner |
| 2026 | CPAIOR | Large Neighborhood Search Meets Iterative Neural Constraint Heuristics. | Yudong W. Xu, Wenhao Li, Scott Sanner, Elias B. Khalil |
| 2026 | SIGIR | CommonWhy: A Dataset for Evaluating Entity-Based Causal Commonsense Reasoning in Large Language Models. | Armin Toroghi, Faeze Moradi Kalarde, Scott Sanner |
| 2025 | AAAI | ModelDiff: Symbolic Dynamic Programming for Model-Aware Policy Transfer in Deep Q-Learning. | Xiaotian Liu, Jihwan Jeong, Ayal Taitler, Michael Gimelfarb, Scott Sanner |
| 2025 | AAAI | ICE-T: Interactions-aware Cross-column Contrastive Embedding for Heterogeneous Tabular Datasets. | Toms Tokr, Scott Sanner |
| 2025 | ACL | Open-World Planning via Lifted Regression with LLM-Inferred Affordances for Embodied Agents. | Xiaotian Liu, Ali Pesaranghader, Hanze Li, Punyaphat Sukcharoenchaikul, Jaehong Kim, Tanmana Sadhu, Hyejeong Jeon, Scott Sanner |
| 2025 | ACL | Q-STRUM Debate: Query-Driven Contrastive Summarization for Recommendation Comparison. | George-Kirollos Saad, Scott Sanner |
| 2025 | CPAIOR | Bounded-Error Policy Optimization for Mixed Discrete-Continuous MDPs via Constraint Generation in Nonlinear Programming. | Michael Gimelfarb, Ayal Taitler, Scott Sanner |
| 2025 | EMNLP | Batched Self-Consistency Improves LLM Relevance Assessment and Ranking. | Anton Korikov, Pan Du, Scott Sanner, Navid Rekabsaz |
| 2025 | EMNLP | MA-DPR: Manifold-aware Distance Metrics for Dense Passage Retrieval. | Yifan Liu, Qianfeng Wen, Mark Zhao, Jiazhou Liang, Scott Sanner |
| 2025 | ICLR | LLM-based Typed Hyperresolution for Commonsense Reasoning with Knowledge Bases. | Armin Toroghi, Ali Pesaranghader, Tanmana Sadhu, Scott Sanner |
| 2025 | ICML | Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction. | Yudong Xu, Wenhao Li, Scott Sanner, Elias Boutros Khalil |
| 2025 | ICML | Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens. | Jihwan Jeong, Xiaoyu Wang, Jingmin Wang, Scott Sanner, Pascal Poupart |
| 2025 | SIGIR | GENNEXT: The Next Generation of IR and Recommender Systems with Language Agents, Generative Models, and Conversational AI. | Yashar Deldjoo, Scott Sanner, Enrico Palumbo, Hugues Bouchard, Shuai Zhang, Pablo Castells, Julian J. McAuley |
| 2025 | SIGIR | CoLoTa: A Dataset for Entity-based Commonsense Reasoning over Long-Tail Knowledge. | Armin Toroghi, Willis Guo, Scott Sanner |
| 2025 | WSDM | Tutorial on Recommendation with Generative Models (Gen-RecSys). | Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, Ren Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano |
| 2024 | AAAI | Bayesian Inference with Complex Knowledge Graph Evidence. | Armin Toroghi, Scott Sanner |
| 2024 | EMNLP | Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answering. | Armin Toroghi, Willis Guo, Mohammad Mahdi Abdollah Pour, Scott Sanner |
| 2024 | EMNLP | Verifiable, Debuggable, and Repairable Commonsense Logical Reasoning via LLM-based Theory Resolution. | Armin Toroghi, Willis Guo, Ali Pesaranghader, Scott Sanner |
| 2024 | ICAPS | JaxPlan and GurobiPlan: Optimization Baselines for Replanning in Discrete and Mixed Discrete-Continuous Probabilistic Domains. | Michael Gimelfarb, Ayal Taitler, Scott Sanner |
| 2024 | KDD | A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). | Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, Ren Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano |
| 2024 | NAACL | Gaussian Process Optimization for Adaptable Multi-Objective Text Generation using Linearly-Weighted Language Models. | Mohammad Mahdi Abdollah Pour, Ali Pesaranghader, Eldan Cohen, Scott Sanner |
| 2024 | RecSys | Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitation. | David Eric Austin, Anton Korikov, Armin Toroghi, Scott Sanner |
| 2024 | RecSys | The 1st International Workshop on Risks, Opportunities, and Evaluation of Generative Models in Recommendation (ROEGEN). | Yashar Deldjoo, Julian J. McAuley, Scott Sanner, Pablo Castells, Shuai Zhang, Enrico Palumbo |
| 2024 | SIGIR | Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking. | Sara Kemper, Justin Cui, Kai Dicarlantonio, Kathy Lin, Danjie Tang, Anton Korikov, Scott Sanner |
| 2023 | AAAI | Scalable and Globally Optimal Generalized L₁ K-center Clustering via Constraint Generation in Mixed Integer Linear Programming. | Aravinth Chembu, Scott Sanner, Hassan Khurram, Akshat Kumar |
| 2023 | AAAI | Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus. | Yudong Xu, Elias B. Khalil, Scott Sanner |
| 2023 | ACL | DiffuDetox: A Mixed Diffusion Model for Text Detoxification. | Griffin Floto, Mohammad Mahdi Abdollah Pour, Parsa Farinneya, Zhenwei Tang, Ali Pesaranghader, Manasa Bharadwaj, Scott Sanner |
| 2023 | CPAIOR | Scalable and Near-Optimal ε-Tube Clusterwise Regression. | Aravinth Chembu, Scott Sanner, Elias B. Khalil |
| 2023 | CPAIOR | A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination. | Jihwan Jeong, Scott Sanner, Akshat Kumar |
| 2023 | ECIR | Self-supervised Contrastive BERT Fine-tuning for Fusion-Based Reviewed-Item Retrieval. | Mohammad Mahdi Abdollah Pour, Parsa Farinneya, Armin Toroghi, Anton Korikov, Ali Pesaranghader, Touqir Sajed, Manasa Bharadwaj, Borislav Mavrin, Scott Sanner |
| 2023 | EMNLP | COUNT: COntrastive UNlikelihood Text Style Transfer for Text Detoxification. | Mohammad Mahdi Abdollah Pour, Parsa Farinneya, Manasa Bharadwaj, Nikhil Verma, Ali Pesaranghader, Scott Sanner |
| 2023 | ICASSP | Towards Dialogue Modeling Beyond Text. | Tongzi Wu, Yuhao Zhou, Wang Ling, Hojin Yang, Joana Veloso, Lin Sun, Ruixin Huang, Norberto Guimaraes, Scott Sanner |
| 2023 | ICLR | Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization. | Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher Abdulhai, Scott Sanner |
| 2023 | RecSys | Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences. | Scott Sanner, Krisztian Balog, Filip Radlinski, Ben Wedin, Lucas Dixon |
| 2023 | SIGIR | LogicRec: Recommendation with Users' Logical Requirements. | Zhenwei Tang, Griffin Floto, Armin Toroghi, Shichao Pei, Xiangliang Zhang, Scott Sanner |
| 2023 | SIGIR | Bayesian Knowledge-driven Critiquing with Indirect Evidence. | Armin Toroghi, Griffin Floto, Zhenwei Tang, Scott Sanner |
| 2023 | SIGIR | Recipe-MPR: A Test Collection for Evaluating Multi-aspect Preference-based Natural Language Retrieval. | Haochen Zhang, Anton Korikov, Parsa Farinneya, Mohammad Mahdi Abdollah Pour, Manasa Bharadwaj, Ali Pesaranghader, Xi Yu Huang, Yi Xin Lok, Zhaoqi Wang, Nathan Jones, Scott Sanner |
| 2022 | AAAI | Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs. | Siow Meng Low, Akshat Kumar, Scott Sanner |
| 2022 | AAAI | A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs. | Noah Patton, Jihwan Jeong, Mike Gimelfarb, Scott Sanner |
| 2022 | ICML | An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming. | Jihwan Jeong, Parth Jaggi, Andrew Butler, Scott Sanner |
| 2022 | RCIS | What's in a (Data) Type? Meaningful Type Safety for Data Science. | Riley Moher, Michael Gruninger, Scott Sanner |
| 2022 | WWW | Distributional Contrastive Embedding for Clarification-based Conversational Critiquing. | Tianshu Shen, Zheda Mai, Ga Wu, Scott Sanner |
| 2022 | SIGIR | Mitigating the Filter Bubble While Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems. | Zhaolin Gao, Tianshu Shen, Zheda Mai, Mohamed Reda Bouadjenek, Isaac Waller, Ashton Anderson, Ron Bodkin, Scott Sanner |
| 2021 | AAAI | Online Class-Incremental Continual Learning with Adversarial Shapley Value. | Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang |
| 2021 | CVPR | Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning. | Zheda Mai, Ruiwen Li, Hyunwoo Kim, Scott Sanner |
| 2021 | IJCAI | Bayesian Experience Reuse for Learning from Multiple Demonstrators. | Mike Gimelfarb, Scott Sanner, Chi-Guhn Lee |
| 2021 | IJCAI | Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions. | Jihwan Jeong, Parth Jaggi, Scott Sanner |
| 2021 | WWW | A Workflow Analysis of Context-driven Conversational Recommendation. | Shengnan Lyu, Arpit Rana, Scott Sanner, Mohamed Reda Bouadjenek |
| 2021 | SIGIR | Bayesian Critiquing with Keyphrase Activation Vectors for VAE-based Recommender Systems. | Hojin Yang, Tianshu Shen, Scott Sanner |
| 2021 | UAI | Contextual policy transfer in reinforcement learning domains via deep mixtures-of-experts. | Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee |
| 2020 | ICDM | Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering. | Zheda Mai, Ga Wu, Kai Luo, Scott Sanner |
| 2020 | RecSys | A Ranking Optimization Approach to Latent Linear Critiquing for Conversational Recommender Systems. | Hanze Li, Scott Sanner, Kai Luo, Ga Wu |
| 2020 | WWW | Latent Linear Critiquing for Conversational Recommender Systems. | Kai Luo, Scott Sanner, Ga Wu, Hanze Li, Hojin Yang |
| 2020 | SIGIR | Deep Critiquing for VAE-based Recommender Systems. | Kai Luo, Hojin Yang, Ga Wu, Scott Sanner |
| 2019 | AAAI | Deep Reactive Policies for Planning in Stochastic Nonlinear Domains. | Thiago Pereira Bueno, Leliane N. de Barros, Denis Deratani Mau, Scott Sanner |
| 2019 | CHIIR | Relevance-driven Clustering for Visual Information Retrieval on Twitter. | Mohamed Reda Bouadjenek, Scott Sanner |
| 2019 | CP | Reward Potentials for Planning with Learned Neural Network Transition Models. | Buser Say, Scott Sanner, Sylvie Thibaux |
| 2019 | CPAIOR | Metric Hybrid Factored Planning in Nonlinear Domains with Constraint Generation. | Buser Say, Scott Sanner |
| 2019 | RecSys | Deep language-based critiquing for recommender systems. | Ga Wu, Kai Luo, Scott Sanner, Harold Soh |
| 2019 | SIGIR | One-Class Collaborative Filtering with the Queryable Variational Autoencoder. | Ga Wu, Mohamed Reda Bouadjenek, Scott Sanner |
| 2019 | SIGIR | Noise Contrastive Estimation for One-Class Collaborative Filtering. | Ga Wu, Maksims Volkovs, Chee Loong Soon, Scott Sanner, Himanshu Rai |
| 2019 | UAI | Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning. | Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee |
| 2019 | SDM | A Novel Regularizer for Temporally Stable Learning with an Application to Twitter Topic Classification. | Yakun Wang, Ga Wu, Mohamed Reda Bouadjenek, Scott Sanner, Sen Su, Zhongbao Zhang |
| 2018 | CPAIOR | Symbolic Bucket Elimination for Piecewise Continuous Constrained Optimization. | Zhijiang Ye, Buser Say, Scott Sanner |
| 2018 | IJCAI | Efficient Symbolic Integration for Probabilistic Inference. | Samuel Kolb, Martin Mladenov, Scott Sanner, Vaishak Belle, Kristian Kersting |
| 2018 | IJCAI | Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models. | Buser Say, Scott Sanner |
| 2018 | RecSys | Two-stage Model for Automatic Playlist Continuation at Scale. | Maksims Volkovs, Himanshu Rai, Zhaoyue Cheng, Ga Wu, Yichao Lu, Scott Sanner |
| 2017 | AAAI | Nonlinear Optimization and Symbolic Dynamic Programming for Parameterized Hybrid Markov Decision Processes. | Shamin Kinathil, Harold Soh, Scott Sanner |
| 2017 | AAAI | Hindsight Optimization for Hybrid State and Action MDPs. | Aswin Raghavan, Scott Sanner, Roni Khardon, Prasad Tadepalli, Alan Fern |
| 2017 | AAAI | Knowledge-Based Provision of Goods and Services for People with Social Needs: Towards a Virtual Marketplace. | Daniela Rosu, Dionne M. Aleman, J. Christopher Beck, Mark H. Chignell, Mariano P. Consens, Mark S. Fox, Michael Gruninger, Chang Liu, Yi Ru, Scott Sanner |
| 2017 | AAAI | Low-Rank Linear Cold-Start Recommendation from Social Data. | Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Lexing Xie, Darius Braziunas |
| 2017 | IJCAI | Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming. | Buser Say, Ga Wu, Yu Qing Zhou, Scott Sanner |
| 2017 | ICWSM | A Longitudinal Study of Topic Classification on Twitter. | Zahra Iman, Scott Sanner, Mohamed Reda Bouadjenek, Lexing Xie |
| 2017 | IUI | Deep Sequential Recommendation for Personalized Adaptive User Interfaces. | Harold Soh, Scott Sanner, Madeleine White, Greg A. Jamieson |
| 2017 | SMC | An open source adaptive user interface for network monitoring. | Sean W. Kortschot, Dusan Sovilj, Harold Soh, Greg A. Jamieson, Scott Sanner, Chelsea Carrasco, Scott Ralph, Scott Langevin |
| 2017 | WWW | Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity. | Marian-Andrei Rizoiu, Lexing Xie, Scott Sanner, Manuel Cebrin, Honglin Yu, Pascal Van Hentenryck |
| 2017 | SoCS | Non-Markovian Rewards Expressed in LTL: Guiding Search Via Reward Shaping. | Alberto Camacho, Oscar Chen, Scott Sanner, Sheila A. McIlraith |
| 2016 | AAAI | Closed-Form Gibbs Sampling for Graphical Models with Algebraic Constraints. | Hadi Mohasel Afshar, Scott Sanner, Christfried Webers |
| 2016 | AAAI | On the Effectiveness of Linear Models for One-Class Collaborative Filtering. | Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Darius Braziunas |
| 2016 | IJCAI | A Symbolic Closed-Form Solution to Sequential Market Making with Inventory. | Shamin Kinathil, Scott Sanner, Sanmay Das, Nicols Della Penna |
| 2016 | IJCAI | Practical Linear Models for Large-Scale One-Class Collaborative Filtering. | Suvash Sedhain, Hung Bui, Jaya Kawale, Nikos Vlassis, Branislav Kveton, Aditya Krishna Menon, Trung Bui, Scott Sanner |
| 2015 | AAAI | Loss-Calibrated Monte Carlo Action Selection. | Ehsan Abbasnejad, Justin Domke, Scott Sanner |
| 2015 | AAAI | Linear-Time Gibbs Sampling in Piecewise Graphical Models. | Hadi Mohasel Afshar, Scott Sanner, Ehsan Abbasnejad |
| 2015 | AAAI | Real-Time Symbolic Dynamic Programming. | Luis Gustavo Rocha Vianna, Leliane N. de Barros, Scott Sanner |
| 2015 | AAAI | Bayesian Model Averaging Naive Bayes (BMA-NB): Averaging over an Exponential Number of Feature Models in Linear Time. | Ga Wu, Scott Sanner, Rodrigo F. S. C. Oliveira |
| 2015 | ICAIL | A study of query reformulation for patent prior art search with partial patent applications. | Mohamed Reda Bouadjenek, Scott Sanner, Gabriela Ferraro |
| 2015 | ICWSM | The Lifecyle of a Youtube Video: Phases, Content and Popularity. | Honglin Yu, Lexing Xie, Scott Sanner |
| 2015 | PAKDD | Context-Aware Detection of Sneaky Vandalism on Wikipedia Across Multiple Languages. | Khoi-Nguyen Tran, Peter Christen, Scott Sanner, Lexing Xie |
| 2015 | WWW | AutoRec: Autoencoders Meet Collaborative Filtering. | Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Lexing Xie |
| 2015 | SIGIR | On Term Selection Techniques for Patent Prior Art Search. | Mona Golestan Far, Scott Sanner, Mohamed Reda Bouadjenek, Gabriela Ferraro, David Hawking |
| 2014 | RecSys | Social collaborative filtering for cold-start recommendations. | Suvash Sedhain, Scott Sanner, Darius Braziunas, Lexing Xie, Jordan Christensen |
| 2014 | UAI | Closed-form Solutions to a Subclass of Continuous Stochastic Games via Symbolic Dynamic Programming. | Shamin Kinathil, Scott Sanner, Nicols Della Penna |
| 2014 | UAI | Sequential Bayesian Optimisation for Spatial-Temporal Monitoring. | Romn Marchant, Fabio Ramos, Scott Sanner |
| 2013 | ICML | Algorithms for Direct 0-1 Loss Optimization in Binary Classification. | Tan Nguyen, Scott Sanner |
| 2013 | IJCAI | Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes. | Ehsan Abbasnejad, Scott Sanner, Edwin V. Bonilla, Pascal Poupart |
| 2013 | IJCAI | Robust Optimization for Hybrid MDPs with State-Dependent Noise. | Zahra Zamani, Scott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros |
| 2013 | SIGIR | Improving LDA topic models for microblogs via tweet pooling and automatic labeling. | Rishabh Mehrotra, Scott Sanner, Wray L. Buntine, Lexing Xie |
| 2013 | UAI | Bounded Approximate Symbolic Dynamic Programming for Hybrid MDPs. | Luis Gustavo Vianna, Scott Sanner, Leliane Nunes de Barros |
| 2012 | AAAI | Symbolic Variable Elimination for Discrete and Continuous Graphical Models. | Scott Sanner, Ehsan Abbasnejad |
| 2012 | AAAI | Symbolic Dynamic Programming for Continuous State and Action MDPs. | Zahra Zamani, Scott Sanner, Cheng Fang |
| 2012 | WWW | New objective functions for social collaborative filtering. | Joseph Noel, Scott Sanner, Khoi-Nguyen Tran, Peter Christen, Lexing Xie, Edwin V. Bonilla, Ehsan Abbasnejad, Nicols Della Penna |
| 2012 | SIGIR | On the mathematical relationship between expected n-call@k and the relevance vs. diversity trade-off. | Kar Wai Lim, Scott Sanner, Shengbo Guo |
| 2011 | CIKM | Diverse retrieval via greedy optimization of expected 1-call@k in a latent subtopic relevance model. | Scott Sanner, Shengbo Guo, Thore Graepel, Sadegh Kharazmi, Sarvnaz Karimi |
| 2011 | IJCAI | Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter. | Babak Ahmadi, Kristian Kersting, Scott Sanner |
| 2011 | UAI | Symbolic Dynamic Programming for Discrete and Continuous State MDPs. | Scott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros |
| 2010 | AAAI | Symbolic Dynamic Programming for First-order POMDPs. | Scott Sanner, Kristian Kersting |
| 2010 | ICML | Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda. | Carlton Downey, Scott Sanner |
| 2010 | ISNN | Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries. | Shengbo Guo, Scott Sanner |
| 2010 | SIGIR | Probabilistic latent maximal marginal relevance. | Shengbo Guo, Scott Sanner |
| 2009 | IJCAI | Bayesian Real-Time Dynamic Programming. | Scott Sanner, Robby Goetschalckx, Kurt Driessens, Guy Shani |
| 2008 | ECAI | Reinforcement Learning with the Use of Costly Features. | Robby Goetschalckx, Scott Sanner, Kurt Driessens |
| 2008 | ICDM | Cost-Sensitive Parsimonious Linear Regression. | Robby Goetschalckx, Kurt Driessens, Scott Sanner |
| 2006 | KR | An Ordered Theory Resolution Calculus for Hybrid Reasoning in First-Order Extensions of Description Logic. | Scott Sanner, Sheila A. McIlraith |
| 2006 | UAI | Practical Linear Value-approximation Techniques for First-order MDPs. | Scott Sanner, Craig Boutilier |
| 2005 | IJCAI | Affine Algebraic Decision Diagrams (AADDs) and their Application to Structured Probabilistic Inference. | Scott Sanner, David A. McAllester |
| 2005 | UAI | Approximate Linear Programming for First-order MDPs. | Scott Sanner, Craig Boutilier |
| 2002 | IROS | Towards object mapping in non-stationary environments with mobile robots. | Rahul Biswas, Benson Limketkai, Scott Sanner, Sebastian Thrun |
| 2000 | ICML | Achieving Efficient and Cognitively Plausible Learning in Backgammon. | Scott Sanner, John R. Anderson, Christian Lebiere, Marsha C. Lovett |