Sanner, Scott

69 publications

NeurIPS 2025 ActiveVOO: Value of Observation Guided Active Knowledge Acquisition for Open-World Embodied Lifted Regression Planning Xiaotian Liu, Ali Pesaranghader, Jaehong Kim, Tanmana Sadhu, Hyejeong Jeon, Scott Sanner

ICLRW 2025 End-to-End Synthesis of Neural Programs in Weight Space Wenhao Li, Yudong Xu, Elias Boutros Khalil, Scott Sanner

AAAI 2025 ICE-T: Interactions-Aware Cross-Column Contrastive Embedding for Heterogeneous Tabular Datasets Tomás Tokár, Scott Sanner

ICLR 2025 LLM-Based Typed Hyperresolution for Commonsense Reasoning with Knowledge Bases Armin Toroghi, Ali Pesaranghader, Tanmana Sadhu, Scott Sanner

AAAI 2025 ModelDiff: Symbolic Dynamic Programming for Model-Aware Policy Transfer in Deep Q-Learning Xiaotian Liu, Jihwan Jeong, Ayal Taitler, Michael Gimelfarb, Scott Sanner

ICML 2025 Reflect-Then-Plan: Offline Model-Based Planning Through a Doubly Bayesian Lens Jihwan Jeong, Xiaoyu Wang, Jingmin Wang, Scott Sanner, Pascal Poupart

ICML 2025 Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction Yudong Xu, Wenhao Li, Scott Sanner, Elias Boutros Khalil

TMLR 2025 Tackling the Abstraction and Reasoning Corpus with Vision Transformers: The Importance of 2D Representation, Positions, and Objects Wenhao Li, Yudong Xu, Scott Sanner, Elias Boutros Khalil

AAAI 2024 Bayesian Inference with Complex Knowledge Graph Evidence Armin Toroghi, Scott Sanner

NeurIPSW 2024 ICE-T: Interactions-Aware Cross-Column Contrastive Embedding for Heterogeneous Tabular Datasets Tomas Tokar, Scott Sanner

TMLR 2024 LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-Based Representations Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, Elias Boutros Khalil

ICLR 2023 Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher Abdulhai, Scott Sanner

ICMLW 2023 Diffusion on the Probability Simplex Griffin Floto, Thorsteinn Jonsson, Mihai Nica, Scott Sanner, Eric Zhengyu Zhu

AAAI 2023 Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus Yudong Xu, Elias B. Khalil, Scott Sanner

AAAI 2023 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

AAAI 2022 A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs Noah Patton, Jihwan Jeong, Mike Gimelfarb, Scott Sanner

ICML 2022 An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming Jihwan Jeong, Parth Jaggi, Andrew Butler, Scott Sanner

MLJ 2022 Arbitrary Conditional Inference in Variational Autoencoders via Fast Prior Network Training Ga Wu, Justin Domke, Scott Sanner

NeurIPSW 2022 Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus Yudong Xu, Elias Boutros Khalil, Scott Sanner

NeurIPS 2022 Learning to Follow Instructions in Text-Based Games Mathieu Tuli, Andrew Li, Pashootan Vaezipoor, Toryn Klassen, Scott Sanner, Sheila McIlraith

AAAI 2022 Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs Siow Meng Low, Akshat Kumar, Scott Sanner

IJCAI 2021 Bayesian Experience Reuse for Learning from Multiple Demonstrators Mike Gimelfarb, Scott Sanner, Chi-Guhn Lee

UAI 2021 Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee

AAAI 2021 Online Class-Incremental Continual Learning with Adversarial Shapley Value Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang

NeurIPS 2021 Representer Point Selection via Local Jacobian Expansion for Post-Hoc Classifier Explanation of Deep Neural Networks and Ensemble Models Yi Sui, Ga Wu, Scott Sanner

NeurIPS 2021 Risk-Aware Transfer in Reinforcement Learning Using Successor Features Michael Gimelfarb, Andre Barreto, Scott Sanner, Chi-Guhn Lee

CVPRW 2021 Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning Zheda Mai, Ruiwen Li, Hyunwoo Kim, Scott Sanner

IJCAI 2021 Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions Jihwan Jeong, Parth Jaggi, Scott Sanner

JAIR 2020 Scalable Planning with Deep Neural Network Learned Transition Models Ga Wu, Buser Say, Scott Sanner

AAAI 2019 Deep Reactive Policies for Planning in Stochastic Nonlinear Domains Thiago Pereira Bueno, Leliane N. de Barros, Denis Deratani Mauá, Scott Sanner

UAI 2019 Epsilon-BMC: A Bayesian Ensemble Approach to Epsilon-Greedy Exploration in Model-Free Reinforcement Learning Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee

IJCAI 2018 Efficient Symbolic Integration for Probabilistic Inference Samuel Kolb, Martin Mladenov, Scott Sanner, Vaishak Belle, Kristian Kersting

IJCAI 2018 Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models Buser Say, Scott Sanner

NeurIPS 2018 Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach Michael Gimelfarb, Scott Sanner, Chi-Guhn Lee

AAAI 2017 Hindsight Optimization for Hybrid State and Action MDPs Aswin Raghavan, Scott Sanner, Roni Khardon, Prasad Tadepalli, Alan Fern

AAAI 2017 Low-Rank Linear Cold-Start Recommendation from Social Data Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Lexing Xie, Darius Braziunas

IJCAI 2017 Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming Buser Say, Ga Wu, Yu Qing Zhou, Scott Sanner

NeurIPS 2017 Scalable Planning with TensorFlow for Hybrid Nonlinear Domains Ga Wu, Buser Say, Scott Sanner

IJCAI 2016 A Symbolic Closed-Form Solution to Sequential Market Making with Inventory Shamin Kinathil, Scott Sanner, Sanmay Das, Nicolás Della Penna

AAAI 2016 Closed-Form Gibbs Sampling for Graphical Models with Algebraic Constraints Hadi Mohasel Afshar, Scott Sanner, Christfried Webers

AAAI 2016 On the Effectiveness of Linear Models for One-Class Collaborative Filtering Suvash Sedhain, Aditya Krishna Menon, Scott Sanner, Darius Braziunas

IJCAI 2016 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

AAAI 2015 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

AAAI 2015 Linear-Time Gibbs Sampling in Piecewise Graphical Models Hadi Mohasel Afshar, Scott Sanner, Ehsan Abbasnejad

AAAI 2015 Loss-Calibrated Monte Carlo Action Selection Ehsan Abbasnejad, Justin Domke, Scott Sanner

AAAI 2015 Real-Time Symbolic Dynamic Programming Luis Gustavo Rocha Vianna, Leliane N. de Barros, Scott Sanner

UAI 2014 Closed-Form Solutions to a Subclass of Continuous Stochastic Games via Symbolic Dynamic Programming Shamin Kinathil, Scott Sanner, Nicolás Della Penna

UAI 2014 Sequential Bayesian Optimisation for Spatial-Temporal Monitoring Román Marchant, Fabio Ramos, Scott Sanner

ICML 2013 Algorithms for Direct 0–1 Loss Optimization in Binary Classification Tan Nguyen, Scott Sanner

UAI 2013 Bounded Approximate Symbolic Dynamic Programming for Hybrid MDPs Luis Gustavo Vianna, Scott Sanner, Leliane Nunes de Barros

ECML-PKDD 2013 Decision-Theoretic Sparsification for Gaussian Process Preference Learning M. Ehsan Abbasnejad, Edwin V. Bonilla, Scott Sanner

IJCAI 2013 Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes Ehsan Abbasnejad, Scott Sanner, Edwin V. Bonilla, Pascal Poupart

IJCAI 2013 Robust Optimization for Hybrid MDPs with State-Dependent Noise Zahra Zamani, Scott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros

ECML-PKDD 2012 Score-Based Bayesian Skill Learning Shengbo Guo, Scott Sanner, Thore Graepel, Wray L. Buntine

AAAI 2012 Symbolic Dynamic Programming for Continuous State and Action MDPs Zahra Zamani, Scott Sanner, Cheng Fang

NeurIPS 2012 Symbolic Dynamic Programming for Continuous State and Observation POMDPs Zahra Zamani, Scott Sanner, Pascal Poupart, Kristian Kersting

AAAI 2012 Symbolic Variable Elimination for Discrete and Continuous Graphical Models Scott Sanner, Ehsan Abbasnejad

IJCAI 2011 Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter Babak Ahmadi, Kristian Kersting, Scott Sanner

ECML-PKDD 2011 Sparse Kernel-SARSA(λ) with an Eligibility Trace Matthew W. Robards, Peter Sunehag, Scott Sanner, Bhaskara Marthi

UAI 2011 Symbolic Dynamic Programming for Discrete and Continuous State MDPs Scott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros

NeurIPS 2010 Gaussian Process Preference Elicitation Shengbo Guo, Scott Sanner, Edwin V. Bonilla

AISTATS 2010 Real-Time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries Shengbo Guo, Scott Sanner

AAAI 2010 Symbolic Dynamic Programming for First-Order POMDPs Scott Sanner, Kristian Kersting

ICML 2010 Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda Carlton Downey, Scott Sanner

IJCAI 2009 Bayesian Real-Time Dynamic Programming Scott Sanner, Robby Goetschalckx, Kurt Driessens, Guy Shani

UAI 2006 Practical Linear Value-Approximation Techniques for First-Order MDPs Scott Sanner, Craig Boutilier

IJCAI 2005 Affine Algebraic Decision Diagrams (AADDs) and Their Application to Structured Probabilistic Inference Scott Sanner, David A. McAllester

UAI 2005 Approximate Linear Programming for First-Order MDPs Scott Sanner, Craig Boutilier

ICML 2000 Achieving Efficient and Cognitively Plausible Learning in Backgammon Scott Sanner, John R. Anderson, Christian Lebiere, Marsha C. Lovett