Paper

1 MAY 2020 to 31 JUL 2021

• Kaifu Wang, Qiang Ning, and Dan Roth. “Learnability with Indirect Supervision Signals.” NeurIPS 2020.
• Jeevana Priya Inala, Yichen Yang, James Paulos, Yewen Pu, Osbert Bastani, Vijay Kumar, Martin Rinard, Armando Solar-Lezama. Neurosymbolic Transformers for Multi-Agent Communication. NeurIPS 2020.
• Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani. Conservative Offline Distributional Reinforcement Learning. NeurIPS 2021.
• Yichen Yang, Jeevana Priya Inala, Osbert Bastani, Yewen Pu, Armando Solar-Lezama, Martin Rinard. Program Synthesis Guided Reinforcement Learning for Partially Observed Environments. NeurIPS (Spotlight) 2021.
• Kishor Jothimurugan, Suguman Bansal, Osbert Bastani, Rajeev Alur. Compositional Reinforcement Learning from Logical Specifications. NeurIPS 2021.
• Sanjay Subramanian, Ben Bogin, Nitish Gupta, Tomer Wolfson, Sameer Singh, Jonathan Berant, and Matt Gardner. “Obtaining Faithful Interpretations from Compositional Neural Networks.” ACL 2020.
• Evangelos Chatzipantazis, Stefanos Pertigkiozolou, Kostas Daniilidis, and Edgar Dobriban. Learning Augmentation Distributions using Transformed Risk Minimization, submitted to NeurIPS 2021.
• Nikolaos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman, Kostas Daniilidis, Probabilistic Modeling for 3D Human Pose Estimation, ICCV 2021.
• Yiannis Kantaros, Taylor Carpenter, Kaustubh Sridhar, Yahan Yang, Insup Lee, and James Weimer. Real-Time Detectors for Digital and Physical Adversarial Inputs to Perception Systems. ICCPS 2021.
• Jorge Mendez, Eric Eaton. Lifelong learning of compositional structures, ICLR 2021.
• Sangdon Park, Shuo Li, Insup Lee, and Osbert Bastani. PAC Confidence Predictions for Deep Neural Network Classifiers. ICLR 2021.
• Radoslav Ivanov, Taylor Carpenter, James Weimer, Rajeev Alur, George Pappas and Insup Lee. Verisig 2.0: Verification of Neural Network Controllers Using Taylor Model Preconditioning. CAV 2021.
• Soham Dan, Michael Zhou, and Dan Roth. "Generalization in Instruction Following Systems." NAACL-HLT 2021.
• Soham Dan, Xinran Han, and Dan Roth. “Compositional Data and Task Augmentation for Instruction Following.” EMNLP-Findings 2021.
• Gupta, Nitish, Sameer Singh, Matt Gardner, and Dan Roth. “Paired Examples as Indirect Supervision in Latent Decision Models.” Submitted.
• Soham Dan, Osbert Bastani, and Dan Roth. “Few-Shot Novel Concept Learning for Semantic Parsing.” EMNLP-Findings 2021.
• Soham Dan, and Dan Roth. “On the Effects of Transformer Size on In- and Out-of-Domain Calibration.” EMNLP-Findings 2021.
• Shuxiao Chen, Koby Crammer, Hangfeng He, Dan Roth, Weijie Su. “Weighted Training for Cross-Task Learning.” arXiv:2105.14095, ICLR 2022.
• Hangfeng He, Mingyuan Zhang, Qiang Ning, Dan Roth. “Foreseeing the Benefits of Incidental Supervision.” EMNLP 2021.
• Philip Huebner, Elior Sulem , Cynthia Fisher, Dan Roth, "BabyBERTa: Learning More Grammar With Small-Scale Child-Directed Language" CoNLL 2021.
• Georgios Georgakis, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Kostas Daniilidis, “Learning to Map for Active Semantic Goal Navigation.” arXiv:2106.15648, ICLR 2022
• Georgios Georgakis, Bernadette Bucher, Anton Arapin, Karl Schmeckpeper, Nikolai Matni, Kostas Daniilidis, “Uncertainty-driven Planner for Exploration and Navigation.” ICRA 2022.
• Seungwon Lee, Sima Behpour, and Eric Eaton. “Sharing less is more: Lifelong learning in deep networks with selective layer transfer.” ICML 2021.

1 AUG 2021 to 31 JUL 2022

• Souradeep Dutta, Kaustubh Sridhar, Osbert Bastani, Edgar Dobriban, James Weimer, Insup Lee, Julia Parish-Morris, "Exploring with Sticky Mittens: Reinforcement Learning with Expert Interventions via Option Templates", CoRL 2022. Submitted.
• R. Kaur, S. Jha, A. Roy, S. Park, E. Dobriban, O. Sokolsky, I. Lee. iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection. AAAI 2022.
• Ramneet Kaur, Kaustubh Sridhar, Sangdon Park, Susmit Jha, Anirban Roy, Oleg Sokolsky, Insup Lee, "CoDiT: Conformal Out-of-Distribution Detection in Time-Series Data", Workshop on PODS at ICML 2022.
• Ramneet Kaur, Kaustubh Sridhar, Sangdon Park, Susmit Jha, Anirban Roy, Oleg Sokolsky, Insup Lee, "CoDiT: Conformal Out-of-Distribution Detection in Time-Series Data", TMLR. Submitted.
• Kaustubh Sridhar, Oleg Sokolsky, Insup Lee, James Weimer, “Improving Neural Network Robustness via Persistency of Excitation”, ACC 2022.
• Kaustubh Sridhar, Souradeep Dutta, Ramneet Kaur, James Weimer, Oleg Sokolsky, Insup Lee, "Towards Alternative Techniques for Improving Adversarial Robustness: Analysis of Adversarial Training at a Spectrum of Perturbations", arXiv:2206.06496.
• Georgios Georgakis, Karl Schmeckpeper, Karan Wanchoo, Sohan Dan, Eleni Miltsakaki, Dan Roth, Kostas Daniilidis, "Cross-modal Map Learning for Vision and Language Navigation." CVPR 2022.
• Yinshuang Xu, Jiahui Lei, Edgar Dobriban, Kostas Daniilidis, "Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces." ICML 2022.
• Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Edgar Dobriban and Kostas Daniilidis, "SE(3)-Equivariant Attention Networks for Shape Reconstruction in Function Space", arXiv:2204.02394 2022.
• V. Lin, R. Ivanov, J. Weimer, O. Sokolsky, I. Lee, "T4V: Exploring Neural Network Architectures that Improve the Scalability of Neural Network Verification." Henzinger-60; Thomas Henzinger Festschrift - Conference Celebrating his 60th Birthday, 2023.
• Soham Dan and Osbert Bastani and Dan Roth, “Understanding Robust Generalization in Learning Regular Languages”, ICML 2022.
• Shuo Li, Xiayan Ji, Edgar Dobriban, Oleg Sokolsky, Insup Lee. PAC-Wrap: Semi-Supervised PAC Anomaly Detection. SIGKDD 2022.
• Shuo Li, Sangdon Park, Xiayan Ji, Insup Lee, Osbert Bastani, “Towards PAC Multi-Object Detection and Tracking”, Workshop on DFUQ at ICML 2022.
• Xiayan Ji, Insup Lee. PAC Guarantee for Detecting Evolving Anomalies in Medical Cyber-physical Systems. ICDM 2022. Submitted.
• Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani, "PAC Prediction Sets Under Covariate Shift", ICLR 2022.
• Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani, "PAC Prediction Sets for Meta-Learning", arXiv:2207.02440 and ICML Workshop on DFUQ 2022.
• Sooyong Jang, Sangdon Park, Insup Lee, Osbert Bastani. "Sequential Covariate Shift Detection Using Classifier Two-Sample Tests." ICML 2022.
• Yahan Yang, Ramneet Kaur, Souradeep Dutta, Insup Lee. Interpretable Detection of Distribution Shifts in Learning Enabled Cyber-Physical Systems. ICCPS 2022.
• Souradeep Dutta, Yahan Yang, Elena Bernardis, Edgar Dobriban, Insup Lee. Memory Classifiers: Two-stage Classification for Robustness in Machine Learning. NeurIPS 2022. Submitted
• Yahan Yang, Soham Dan, Dan Roth, Insup Lee. In and Out-of Domain Text Adversarial Robustness via Label Smoothing. EMNLP 2022. Submitted. 
• Meghna Gummadi, David Kent, Jorge Mendez, Eric Eaton.. “SHELS: Exclusive feature sets for novelty detection and continual learning without class boundaries.” CoLLAs 2022.
• Marcel Hussing, Jorge Mendez, Meghna Gummadi, Eric Eaton. “CompoSuite: A compositional reinforcement learning benchmark.” CoLLAs 2022.
• Jorge Mendez, Harm van Seijen, and Eric Eaton. (2022). “Modular lifelong reinforcement learning via neural composition.” ICLR 2022.