| 2026 | AIME | Learning to Segment Using Summary Statistics and Weak Supervision. | Omkar Kulkarni, Edward Raff, Tim Oates |
| 2025 | IJCNN | DeBUGCN - Detecting Backdoors in CNNs Using Graph Convolutional Networks. | Akash Vartak, Khondoker Murad Hossain, Tim Oates |
| 2024 | AISTATS | Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection. | Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt |
| 2024 | FlAIRS | Using LLMs for Augmenting Hierarchical Agents with Common Sense Priors. | Bharat Prakash, Tim Oates, Tinoosh Mohsenin |
| 2024 | ICASSP | Ten-Guard: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networks. | Khondoker Murad Hossain, Tim Oates |
| 2023 | AAAI | Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks. | Khondoker Murad Hossain, Tim Oates |
| 2023 | AAAI | RFC-Net: Learning High Resolution Global Features for Medical Image Segmentation on a Computational Budget (Student Abstract). | Sourajit Saha, Shaswati Saha, Md. Osman Gani, Tim Oates, David Chapman |
| 2023 | FMCAD | Towards a Correct-by-Construction Design of Integrated Modular Avionics. | Baoluo Meng, Joyanta Debnath, Sarat Chandra Varanasi, Emmanuel Manoloios, Michael Durling, Saswata Paul, Daniel Prince, Saif Alsabbagh, Richard Haadsma, Craig McMillan, Chi Zhang, Tim Oates |
| 2023 | ICML | Recasting Self-Attention with Holographic Reduced Representations. | Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt |
| 2022 | ICML | Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations. | Mohammad Mahmudul Alam, Edward Raff, Tim Oates, James Holt |
| 2021 | AAAI | Bringing UMAP Closer to the Speed of Light with GPU Acceleration. | Corey J. Nolet, Victor Lafargue, Edward Raff, Thejaswi Nanditale, Tim Oates, John Zedlewski, Joshua Patterson |
| 2021 | ACL | Learning a Reversible Embedding Mapping using Bi-Directional Manifold Alignment. | Ashwinkumar Ganesan, Francis Ferraro, Tim Oates |
| 2021 | ADMA | Predicting Network Threat Events Using HMM Ensembles. | Akshay Peshave, Ashwinkumar Ganesan, Tim Oates |
| 2020 | AAAI | Guiding Safe Reinforcement Learning Policies Using Structured Language Constraints. | Bharat Prakash, Nicholas R. Waytowich, Ashwinkumar Ganesan, Tim Oates, Tinoosh Mohsenin |
| 2020 | ICDM | Immigration Document Classification and Automated Response Generation. | Sourav Mukherjee, Tim Oates, Vince DiMascio, Huguens Jean, Rob Ares, David Widmark, Jaclyn Harder |
| 2019 | ICCBR | NOD-CC: A Hybrid CBR-CNN Architecture for Novel Object Discovery. | J. T. Turner, Michael W. Floyd, Kalyan Moy Gupta, Tim Oates |
| 2019 | ICRA | Inferring Robot Morphology from Observation of Unscripted Movement. | Neil Bell, Brian Seipp, Tim Oates, Cynthia Matuszek |
| 2019 | ISVC | Improving Visual Reasoning with Attention Alignment. | Komal Sharan, Ashwinkumar Ganesan, Tim Oates |
| 2018 | PAKDD | Denoising Time Series Data Using Asymmetric Generative Adversarial Networks. | Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, W. David Hairston |
| 2018 | SIGIR | Large Scale Taxonomy Classification using BiLSTM with Self-Attention. | Hang Gao, Tim Oates |
| 2017 | CEC | Neuroevolution-based Inverse Reinforcement Learning. | Karan K. Budhraja, Tim Oates |
| 2017 | HRI | Preliminary Survey Analysis in Participatory Design: Repositioning, Transferring, and Personal Care Robots. | Kavita Krishnaswamy, Srinivas Moorthy, Tim Oates |
| 2017 | ICDM | Dataset Selection for Controlling Swarms by Visual Demonstration. | Karan Kumar Budhraja, Tim Oates |
| 2017 | IJCNN | Identifying spatial relations in images using convolutional neural networks. | Mandar Haldekar, Ashwinkumar Ganesan, Tim Oates |
| 2017 | IJCNN | Connecting deep neural networks with symbolic knowledge. | Arjun Kumar, Tim Oates |
| 2017 | IJCNN | Visual entity linking. | Neha Tilak, Sunil Gandhi, Tim Oates |
| 2017 | IJCNN | Time series classification from scratch with deep neural networks: A strong baseline. | Zhiguang Wang, Weizhong Yan, Tim Oates |
| 2017 | ISCAS | An EEG artifact identification embedded system using ICA and multi-instance learning. | Ali Jafari, Sunil Gandhi, Sri Harsha Konuru, W. David Hairston, Tim Oates, Tinoosh Mohsenin |
| 2016 | AAAI | Adaptive Normalized Risk-Averting Training for Deep Neural Networks. | Zhiguang Wang, Tim Oates, James Lo |
| 2016 | EDBT | RPM: Representative Pattern Mining for Efficient Time Series Classification. | Xing Wang, Jessica Lin, Pavel Senin, Tim Oates, Sunil Gandhi, Arnold P. Boedihardjo, Crystal Chen, Susan Frankenstein |
| 2016 | ICDM | Feature Selection in Environments with Limited Voluntary Information Sharing. | Nicholay Topin, Karan K. Budhraja, Tim Oates |
| 2016 | IRI | A Data Driven Approach for the Science of Cyber Security: Challenges and Directions. | Bhavani Thuraisingham, Murat Kantarcioglu, Kevin W. Hamlen, Latifur Khan, Tim Finin, Anupam Joshi, Tim Oates, Elisa Bertino |
| 2016 | LREC | A Gold Standard for Scalar Adjectives. | Bryan Wilkinson, Tim Oates |
| 2015 | CIKM | A Generative Model For Time Series Discretization Based On Multiple Normal Distributions. | Sunil Gandhi, Tim Oates, Arnold P. Boedihardjo, Crystal Chen, Jessica Lin, Pavel Senin, Susan Frankenstein, Xing Wang |
| 2015 | EDBT | Time series anomaly discovery with grammar-based compression. | Pavel Senin, Jessica Lin, Xing Wang, Tim Oates, Sunil Gandhi, Arnold P. Boedihardjo, Crystal Chen, Susan Frankenstein |
| 2015 | FlAIRS | Pooling SAX-BoP Approaches with Boosting to Classify Multivariate Synchronous Physiological Time Series Data. | Zhiguang Wang, Tim Oates |
| 2015 | ICDM | Adversarial Feature Selection. | Karan Kumar Budhraja, Tim Oates |
| 2015 | IJCAI | Imaging Time-Series to Improve Classification and Imputation. | Zhiguang Wang, Tim Oates |
| 2014 | FlAIRS | Comparing Raw Data and Feature Extraction for Seizure Detection with Deep Learning Methods. | Adam Page, J. T. Turner, Tinoosh Mohsenin, Tim Oates |
| 2014 | ICDM | Text Mining for Hypotheses and Results in Translational Medicine Studies. | Terry H. Tsai, Niels Kasch, Craig Pfeifer, Tim Oates |
| 2014 | ICMLA | On-Line Signature Verification Using Symbolic Aggregate Approximation (SAX) and Sequential Mining Optimization (SMO). | Rakesh Deivachilai, Tim Oates |
| 2014 | ICMLA | Time Warping Symbolic Aggregation Approximation with Bag-of-Patterns Representation for Time Series Classification. | Zhiguang Wang, Tim Oates |
| 2013 | CIKM | Motif discovery in spatial trajectories using grammar inference. | Tim Oates, Arnold P. Boedihardjo, Jessica Lin, Crystal Chen, Susan Frankenstein, Sunil Gandhi |
| 2013 | ICMLA | Ecosembles: A Rapidly Deployable Image Classification System Using Feature-Views. | Adrian Rosebrock, Tim Oates, Jesus J. Caban |
| 2013 | ICTAI | From Robots to Reinforcement Learning. | Tongchun Du, Michael T. Cox, Don Perlis, Jared Shamwell, Tim Oates |
| 2013 | NAACL | KELVIN: a tool for automated knowledge base construction. | Paul McNamee, James Mayfield, Tim Finin, Tim Oates, Dawn J. Lawrie, Tan Xu, Douglas W. Oard |
| 2012 | ICMLA | Predicting Patient Outcomes from a Few Hours of High Resolution Vital Signs Data. | Tim Oates, Colin F. Mackenzie, Lynn G. Stansbury, Bizhan Aarabi, Deborah M. Stein, Peter Fu-Ming Hu |
| 2012 | ICMLA | Exploiting Representational Diversity for Time Series Classification. | Tim Oates, Colin F. Mackenzie, Deborah M. Stein, Lynn G. Stansbury, Joseph Dubose, Bizhan Aarabi, Peter Fu-Ming Hu |
| 2012 | IRI | Finding story chains in newswire articles. | Xianshu Zhu, Tim Oates |
| 2012 | NAACL | A Context-Aware Approach to Entity Linking. | Veselin Stoyanov, James Mayfield, Tan Xu, Douglas W. Oard, Dawn J. Lawrie, Tim Oates, Tim Finin |
| 2012 | SDM | Visualizing Variable-Length Time Series Motifs. | Yuan Li, Jessica Lin, Tim Oates |
| 2011 | ICDM | Using Modified Multivariate Bag-of-Words Models to Classify Physiological Data. | Patricia Ordez, Tom Armstrong, Tim Oates, Jim Fackler |
| 2011 | ICMLA | Classification of Patients Using Novel Multivariate Time Series Representations of Physiological Data. | Patricia Ordez, Tom Armstrong, Tim Oates, Jim Fackler |
| 2011 | ICMLA | Improving the Discovery and Characterization of Hidden Variables by Regularizing the LO-net. | Soumi Ray, Tim Oates |
| 2011 | ICTAI | Managing Uncertainty in Text-to-Sketch Tracking Problems. | Matthew D. Schmill, Tim Oates |
| 2010 | AAAI | Metacognition for Detecting and Resolving Conflicts in Operational Policies. | Darsana P. Josyula, Bette J. Donahue, Matthew McCaslin, Michelle Snowden, Michael L. Anderson, Tim Oates, Matthew D. Schmill, Donald Perlis |
| 2010 | EMNLP | We're Not in Kansas Anymore: Detecting Domain Changes in Streams. | Mark Dredze, Tim Oates, Christine D. Piatko |
| 2010 | ICMLA | Discovering and Characterizing Hidden Variables in Streaming Multivariate Time Series. | Soumi Ray, Tim Oates |
| 2010 | LCN | Energy efficient node engagement strategies for achieving data fidelity in wireless sensor networks. | Namita Sapre, Mohamed F. Younis, Tim Oates |
| 2010 | SDM | Inferring Probability Distributions of Graph Size and Node Degree from Stochastic Graph Grammars. | Sourav Mukherjee, Tim Oates |
| 2009 | CIKM | Ensembles in adversarial classification for spam. | Deepak Chinavle, Pranam Kolari, Tim Oates, Tim Finin |
| 2009 | IJCAI | A Context Driven Approach for Workflow Mining. | Fusun Yaman, Tim Oates, Mark H. Burstein |
| 2008 | AAAI | Lexical and Grammatical Inference. | Tom Armstrong, Tim Oates |
| 2008 | FlAIRS | Learning in the Lexical-Grammatical Interface. | Tom Armstrong, Tim Oates |
| 2007 | AAAI | UNDERTOW: Multi-Level Segmentation of Real-Valued Time Series. | Tom Armstrong, Tim Oates |
| 2007 | AAAI | Real-Time Identification of Operating Room State from Video. | Beenish Bhatia, Tim Oates, Yan Xiao, Peter Fu-Ming Hu |
| 2007 | AAAI | The Marchitecture: A Cognitive Architecture for a Robot Baby. | Marc Pickett, Tim Oates |
| 2007 | IJCAI | A Human Activity Aware Learning Mobile Music Player. | Sandor Dornbush, Anupam Joshi, Zary Segall, Tim Oates |
| 2007 | IJCAI | Using Ontologies and the Web to Learn Lexical Semantics. | Aarti Gupta, Tim Oates |
| 2007 | ICWSM | Feeds That Matter: A Study of Bloglines Subscriptions. | Akshay Java, Pranam Kolari, Tim Finin, Anupam Joshi, Tim Oates |
| 2006 | AAAI | Detecting Spam Blogs: A Machine Learning Approach. | Pranam Kolari, Akshay Java, Tim Finin, Tim Oates, Anupam Joshi |
| 2006 | FUSION | Visualization Support for Fusing Relational, Spatio-Temporal Data: Building Career Histories. | Jim Blythe, Mithila Patwardhan, Tim Oates, Marie desJardins, Penny Rheingans |
| 2005 | AAAI | Discovering Domain-Specific Composite Kernels. | Tom Briggs, Tim Oates |
| 2005 | IJCAI | Transfer in Learning by Doing. | William Krueger, Tim Oates, Tom Armstrong, Paul R. Cohen, Carole R. Beal |
| 2004 | AAAI | On the Relationship between Lexical Semantics and Syntax for the Inference of Context-Free Grammars. | Tim Oates, Tom Armstrong, Justin Harris, Mark Nejman |
| 2004 | WAW | Generating Web Graphs with Embedded Communities. | Vivek Tawde, Tim Oates, Eric J. Glover |
| 2003 | ILP | Estimating Maximum Likelihood Parameters for Stochastic Context-Free Graph Grammars. | Tim Oates, Shailesh Doshi, Fang Huang |
| 2002 | AAAI | Contentful Mental States for Robot Baby. | Paul R. Cohen, Tim Oates, Carole R. Beal, Niall M. Adams |
| 2002 | ICDM | PERUSE: An Unsupervised Algorithm for Finding Recurrig Patterns in Time Series. | Tim Oates |
| 2002 | ICML | Learning k-Reversible Context-Free Grammars from Positive Structural Examples. | Tim Oates, Devina Desai, Vinay Bhat |
| 2002 | UAI | The Thing that we Tried Didn't Work very Well: Deictic Representation in Reinforcement Learning. | Sarah Finney, Natalia Gardiol, Leslie Pack Kaelbling, Tim Oates |
| 2001 | AI | The Importance of Being Discrete: Learning Classes of Actions and Outcomes through Interaction. | Gary W. King, Tim Oates |
| 2001 | ALT | Robot Baby 2001. | Paul R. Cohen, Tim Oates, Niall M. Adams, Carole R. Beal |
| 2001 | DIS | Robot Baby 2001. | Paul R. Cohen, Tim Oates, Niall M. Adams, Carole R. Beal |
| 2000 | AAAI | A Method for Clustering the Experiences of a Mobile Robot that Accords with Human Judgments. | Tim Oates, Matthew D. Schmill, Paul R. Cohen |
| 1999 | AAAI | Toward a Theoretical Understanding of Why and When Decision Tree Pruning Algorithms Fail. | Tim Oates, David D. Jensen |
| 1999 | AISTATS | Efficient mining of statistical dependencies. | Tim Oates, Matthew D. Schmill, Paul R. Cohen, Casey Durfee |
| 1999 | AISTATS | Learned models for continuous planning. | Matthew D. Schmill, Tim Oates, Paul R. Cohen |
| 1999 | IJCAI | Efficient Mining of Statistical Dependencies. | Tim Oates, Matthew D. Schmill, Paul R. Cohen |
| 1999 | KDD | Identifying Distinctive Subsequences in Multivariate Time Series by Clustering. | Tim Oates |
| 1999 | KDD | Efficient Progressive Sampling. | Foster J. Provost, David D. Jensen, Tim Oates |
| 1998 | KDD | Large Datasets Lead to Overly Complex Models: An Explanation and a Solution. | Tim Oates, David D. Jensen |
| 1997 | AISTATS | The Effects of Training Set Size on Decision Tree Complexity. | Tim Oates, David D. Jensen |
| 1997 | AISTATS | A Family of Algorithms for Finding Temporal Structure in Data. | Tim Oates, Matthew D. Schmill, David D. Jensen, Paul R. Cohen |
| 1997 | ICML | The Effects of Training Set Size on Decision Tree Complexity. | Tim Oates, David D. Jensen |
| 1997 | IDA | Building Simple Models: A Case Study with Decision Trees. | David D. Jensen, Tim Oates, Paul R. Cohen |
| 1996 | AAAI | Searching for Planning Operators with Context-Dependent and Probabilistic Effects. | Tim Oates, Paul R. Cohen |
| 1996 | ICML | Searching for Structure in Multiple Streams of Data. | Tim Oates, Paul R. Cohen |
| 1995 | AISTATS | Detecting Complex Dependencies in Categorical Data. | Tim Oates, Matthew D. Schmill, Dawn E. Gregory, Paul R. Cohen |
| 1995 | ICTAI | Tools for detecting dependencies in AI systems. | Matthew D. Schmill, Tim Oates, Paul R. Cohen |