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ORCIDTim Oates 0001
Timothy Oates 0001
Person information
- affiliation: University of Maryland Baltimore County, Baltimore, MD, USA
- affiliation: Synaptiq, USA
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2020 – today
- 2024
[c158]Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt:
Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection. AISTATS 2024: 4042-4050- [c157]Bharat Prakash, Tim Oates, Tinoosh Mohsenin:
Using LLMs for Augmenting Hierarchical Agents with Common Sense Priors. FLAIRS 2024 - [c156]Khondoker Murad Hossain, Tim Oates:
Ten-Guard: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networks. ICASSP 2024: 7080-7084 - [c155]Khondoker Murad Hossain, Tim Oates:
Advancing Security in AI Systems: A Novel Approach to Detecting Backdoors in Deep Neural Networks. ICC 2024: 740-745 - [i44]Khondoker Murad Hossain, Tim Oates:
TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networks. CoRR abs/2401.05432 (2024) - [i43]Khondoker Murad Hossain, Tim Oates:
Advancing Security in AI Systems: A Novel Approach to Detecting Backdoors in Deep Neural Networks. CoRR abs/2403.08208 (2024) - [i42]Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt:
Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection. CoRR abs/2403.17978 (2024) - 2023
- [c154]Khondoker Murad Hossain, Tim Oates:
Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks. SafeAI@AAAI 2023 - [c153]Sourajit Saha, Shaswati Saha, Md. Osman Gani, Tim Oates, David Chapman:
RFC-Net: Learning High Resolution Global Features for Medical Image Segmentation on a Computational Budget (Student Abstract). AAAI 2023: 16314-16315 - [c152]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:
Towards a Correct-by-Construction Design of Integrated Modular Avionics. FMCAD 2023: 221-227 - [c151]Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt:
Recasting Self-Attention with Holographic Reduced Representations. ICML 2023: 490-507 - [c150]Corey J. Nolet, Divye Gala, Alexandre Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates:
cuSLINK: Single-Linkage Agglomerative Clustering on the GPU. ECML/PKDD (1) 2023: 711-726 - [i41]Sourajit Saha, Shaswati Saha, Md. Osman Gani, Tim Oates, David Chapman:
RFC-Net: Learning High Resolution Global Features for Medical Image Segmentation on a Computational Budget. CoRR abs/2302.06134 (2023) - [i40]Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt:
Recasting Self-Attention with Holographic Reduced Representations. CoRR abs/2305.19534 (2023) - [i39]Corey J. Nolet, Divye Gala, Alexandre Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates:
cuSLINK: Single-linkage Agglomerative Clustering on the GPU. CoRR abs/2306.16354 (2023) - [i38]Bharat Prakash, Tim Oates, Tinoosh Mohsenin:
LLM Augmented Hierarchical Agents. CoRR abs/2311.05596 (2023) - [i37]Mohammad Mahmudul Alam, Edward Raff, Tim Oates, Cynthia Matuszek:
DDxT: Deep Generative Transformer Models for Differential Diagnosis. CoRR abs/2312.01242 (2023) - [i36]Mohammad Mahmudul Alam, Edward Raff, Tim Oates:
Towards Generalization in Subitizing with Neuro-Symbolic Loss using Holographic Reduced Representations. CoRR abs/2312.15310 (2023) - 2022
- [j24]Aidin Shiri
, Uttej Kallakuri, Hasib-Al Rashid, Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
E2HRL: An Energy-efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. ACM Trans. Design Autom. Electr. Syst. 27(5): 45:1-45:19 (2022) - [c149]Rebecca Saul, Mohammad Mahmudul Alam, John Hurwitz, Edward Raff, Tim Oates, James Holt:
Lempel-Ziv Networks. ICBINB 2022: 1-11 - [c148]Mohammad Mahmudul Alam, Edward Raff, Tim Oates, James Holt:
Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations. ICML 2022: 367-393 - [c147]Corey J. Nolet, Divye Gala, Edward Raff, Joe Eaton, Brad Rees, Tim Oates:
GPU Semiring Primitives for Sparse Neighborhood Methods. MLSys 2022 - [i35]Mohammad Mahmudul Alam, Edward Raff, Tim Oates, James Holt:
Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations. CoRR abs/2206.05893 (2022) - [i34]Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
Towards an Interpretable Hierarchical Agent Framework using Semantic Goals. CoRR abs/2210.08412 (2022) - [i33]Rebecca Saul, Mohammad Mahmudul Alam, John Hurwitz, Edward Raff, Tim Oates, James Holt:
Lempel-Ziv Networks. CoRR abs/2211.13250 (2022) - [i32]Khondoker Murad Hossain, Tim Oates:
Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks. CoRR abs/2212.08121 (2022) - 2021
- [c146]Corey J. Nolet, Victor Lafargue, Edward Raff, Thejaswi Nanditale, Tim Oates, John Zedlewski, Joshua Patterson:
Bringing UMAP Closer to the Speed of Light with GPU Acceleration. AAAI 2021: 418-426 - [c145]Ashwinkumar Ganesan, Francis Ferraro, Tim Oates:
Learning a Reversible Embedding Mapping using Bi-Directional Manifold Alignment. ACL/IJCNLP (Findings) 2021: 3132-3139 - [c144]Akshay Peshave, Ashwinkumar Ganesan, Tim Oates:
Predicting Network Threat Events Using HMM Ensembles. ADMA 2021: 229-240 - [c143]Aidin Shiri, Bharat Prakash, Arnab Neelim Mazumder, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
An Energy-Efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. AICAS 2021: 1-4 - [c142]Sourav Mukherjee, J. J. Ben-Joseph, Marcelo Campos, Prashan Malla, Hieu Nguyen, Anh Pham, Tim Oates, Vasudevan Janarthanan:
Predicting Physiological Effects of Chemical Substances Using Natural Language Processing. CCECE 2021: 1-6 - [c141]Sourav Mukherjee, David Widmark, Vince DiMascio, Tim Oates:
Determining Standard Occupational Classification Codes from Job Descriptions in Immigration Petitions. ICDM (Workshops) 2021: 647-652 - [c140]Ashwinkumar Ganesan, Hang Gao, Sunil Gandhi, Edward Raff, Tim Oates, James Holt, Mark McLean:
Learning with Holographic Reduced Representations. NeurIPS 2021: 25606-25620 - [i31]Corey J. Nolet, Divye Gala, Edward Raff, Joe Eaton, Brad Rees, John Zedlewski, Tim Oates:
Semiring Primitives for Sparse Neighborhood Methods on the GPU. CoRR abs/2104.06357 (2021) - [i30]Ashwinkumar Ganesan, Francis Ferraro, Tim Oates:
Learning a Reversible Embedding Mapping using Bi-Directional Manifold Alignment. CoRR abs/2107.00124 (2021) - [i29]Ashwinkumar Ganesan, Hang Gao, Sunil Gandhi, Edward Raff, Tim Oates, James Holt, Mark McLean:
Learning with Holographic Reduced Representations. CoRR abs/2109.02157 (2021) - [i28]Sourav Mukherjee, David Widmark, Vince DiMascio, Tim Oates:
Determining Standard Occupational Classification Codes from Job Descriptions in Immigration Petitions. CoRR abs/2110.00078 (2021) - [i27]Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
Interactive Hierarchical Guidance using Language. CoRR abs/2110.04649 (2021) - [i26]Bharat Prakash, Nicholas R. Waytowich, Tinoosh Mohsenin, Tim Oates:
Automatic Goal Generation using Dynamical Distance Learning. CoRR abs/2111.04120 (2021) - 2020
- [c139]Bharat Prakash, Nicholas R. Waytowich, Ashwinkumar Ganesan, Tim Oates, Tinoosh Mohsenin:
Guiding Safe Reinforcement Learning Policies Using Structured Language Constraints. SafeAI@AAAI 2020: 153-161 - [c138]Sourav Mukherjee, Tim Oates, Vince DiMascio, Huguens Jean, Rob Ares, David Widmark, Jaclyn Harder:
Immigration Document Classification and Automated Response Generation. ICDM (Workshops) 2020: 782-789 - [i25]Ashwinkumar Ganesan, Frank Ferraro, Tim Oates:
Locality Preserving Loss to Align Vector Spaces. CoRR abs/2004.03734 (2020) - [i24]Corey J. Nolet, Victor Lafargue, Edward Raff, Thejaswi Nanditale, Tim Oates, John Zedlewski, Joshua Patterson:
Bringing UMAP Closer to the Speed of Light with GPU Acceleration. CoRR abs/2008.00325 (2020) - [i23]Sourav Mukherjee, Tim Oates, Vince DiMascio, Huguens Jean, Rob Ares, David Widmark, Jaclyn Harder:
Immigration Document Classification and Automated Response Generation. CoRR abs/2010.01997 (2020)
2010 – 2019
- 2019
- [j23]Ali Jafari, Ashwinkumar Ganesan, Chetan Sai Kumar Thalisetty, Varun Sivasubramanian, Tim Oates, Tinoosh Mohsenin:
SensorNet: A Scalable and Low-Power Deep Convolutional Neural Network for Multimodal Data Classification. IEEE Trans. Circuits Syst. I Regul. Pap. 66-I(1): 274-287 (2019) - [c137]Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, Nicholas R. Waytowich:
Learning Behaviors from a Single Video Demonstration Using Human Feedback. AAMAS 2019: 1970-1972 - [c136]Bharat Prakash, Mark Horton, Nicholas R. Waytowich, William David Hairston, Tim Oates, Tinoosh Mohsenin:
On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning. ACM Great Lakes Symposium on VLSI 2019: 507-512 - [c135]J. T. Turner, Michael W. Floyd, Kalyan Moy Gupta, Tim Oates:
NOD-CC: A Hybrid CBR-CNN Architecture for Novel Object Discovery. ICCBR 2019: 373-387 - [c134]Neil Bell, Brian Seipp, Tim Oates, Cynthia Matuszek:
Inferring Robot Morphology from Observation of Unscripted Movement. ICRA 2019: 9544-9551 - [c133]Komal Sharan, Ashwinkumar Ganesan, Tim Oates:
Improving Visual Reasoning with Attention Alignment. ISVC (1) 2019: 219-230 - [i22]Bharat Prakash, Mark Horton, Nicholas R. Waytowich, William David Hairston, Tim Oates, Tinoosh Mohsenin:
On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning. CoRR abs/1903.10404 (2019) - [i21]Ashwinkumar Ganesan, Pooja Parameshwarappa, Akshay Peshave, Zhiyuan Chen, Tim Oates:
Extending Signature-based Intrusion Detection Systems WithBayesian Abductive Reasoning. CoRR abs/1903.12101 (2019) - [i20]Isaac Mativo, Yelena Yesha, Michael A. Grasso, Tim Oates, Qian Zhu:
Hybrid Mortality Prediction using Multiple Source Systems. CoRR abs/1905.00752 (2019) - [i19]Sourav Mukherjee, Tim Oates, Ryan Wright:
Graph Node Embeddings using Domain-Aware Biased Random Walks. CoRR abs/1908.02947 (2019) - [i18]Chi Zhang, Bryan Wilkinson, Ashwinkumar Ganesan, Tim Oates:
Determining the Scale of Impact from Denial-of-Service Attacks in Real Time Using Twitter. CoRR abs/1909.05890 (2019) - [i17]Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, Nicholas R. Waytowich:
Learning from Observations Using a Single Video Demonstration and Human Feedback. CoRR abs/1909.13392 (2019) - [i16]Hang Gao, Tim Oates:
Universal Adversarial Perturbation for Text Classification. CoRR abs/1910.04618 (2019) - [i15]Karan K. Budhraja, Hang Gao, Tim Oates:
Using Neural Networks for Programming by Demonstration. CoRR abs/1910.04724 (2019) - 2018
- [j22]Pavel Senin, Jessica Lin, Xing Wang, Tim Oates, Sunil Gandhi, Arnold P. Boedihardjo, Crystal Chen, Susan Frankenstein:
GrammarViz 3.0: Interactive Discovery of Variable-Length Time Series Patterns. ACM Trans. Knowl. Discov. Data 12(1): 10:1-10:28 (2018) - [c132]Sandeep Nair Narayanan, Ashwinkumar Ganesan, Karuna P. Joshi, Tim Oates, Anupam Joshi, Tim Finin:
Early Detection of Cybersecurity Threats Using Collaborative Cognition. CIC 2018: 354-363 - [c131]Sunil Gandhi, Tim Oates, Tinoosh Mohsenin, W. David Hairston:
Denoising Time Series Data Using Asymmetric Generative Adversarial Networks. PAKDD (3) 2018: 285-296 - [c130]Hang Gao, Tim Oates:
On Finer Control of Information Flow in LSTMs. ECML/PKDD (1) 2018: 527-540 - [c129]Brian Seipp, Karan Kumar Budhraja, Tim Oates:
Optimizing Transitions between Abstract ABM Demonstrations. SASO 2018: 100-109 - [c128]Karan Kumar Budhraja, Tim Oates:
Improved Reverse Mapping for Controlling Swarms by Visual Demonstration. FAS*W@SASO/ICAC 2018: 130-135 - [c127]Karan Kumar Budhraja, Tim Oates:
Implementing Feedback for Programming by Demonstration. SASO 2018: 162-167 - [c126]Hang Gao, Tim Oates:
Large Scale Taxonomy Classification using BiLSTM with Self-Attention. eCOM@SIGIR 2018 - [i14]Sandeep Nair Narayanan, Ashwinkumar Ganesan, Karuna P. Joshi, Tim Oates, Anupam Joshi, Tim Finin:
Cognitive Techniques for Early Detection of Cybersecurity Events. CoRR abs/1808.00116 (2018) - 2017
- [j21]Karan K. Budhraja, John Winder, Tim Oates:
Feature Construction for Controlling Swarms by Visual Demonstration. ACM Trans. Auton. Adapt. Syst. 12(2): 10:1-10:22 (2017) - [c125]Karan K. Budhraja, Tim Oates:
Neuroevolution-based Inverse Reinforcement Learning. CEC 2017: 67-76 - [c124]Kavita Krishnaswamy, Srinivas Moorthy, Tim Oates:
Preliminary Survey Analysis in Participatory Design: Repositioning, Transferring, and Personal Care Robots. HRI (Companion) 2017: 171-172 - [c123]Karan Kumar Budhraja, Tim Oates:
Dataset Selection for Controlling Swarms by Visual Demonstration. ICDM Workshops 2017: 932-941 - [c122]Neha Tilak, Sunil Gandhi, Tim Oates:
Visual entity linking. IJCNN 2017: 665-672 - [c121]Zhiguang Wang, Weizhong Yan, Tim Oates:
Time series classification from scratch with deep neural networks: A strong baseline. IJCNN 2017: 1578-1585 - [c120]Mandar Haldekar, Ashwinkumar Ganesan, Tim Oates:
Identifying spatial relations in images using convolutional neural networks. IJCNN 2017: 3593-3600 - [c119]Arjun Kumar, Tim Oates:
Connecting deep neural networks with symbolic knowledge. IJCNN 2017: 3601-3608 - [c118]Ali Jafari, Sunil Gandhi, Sri Harsha Konuru, W. David Hairston, Tim Oates, Tinoosh Mohsenin:
An EEG artifact identification embedded system using ICA and multi-instance learning. ISCAS 2017: 1-4 - [c117]Kavita Krishnaswamy, Srinivas Moorthy, Tim Oates:
Survey Data Analysis for Repositioning, Transferring, and Personal Care Robots. PETRA 2017: 45-51 - [c116]Crystal Chen, Arnold P. Boedihardjo, Brian S. Jenkins, Charlotte L. Ellison, Jessica Lin, Pavel Senin, Tim Oates:
STAVIS 2.0: Mining Spatial Trajectories via Motifs. SSTD 2017: 433-439 - [i13]Mandar Haldekar, Ashwinkumar Ganesan, Tim Oates:
Identifying Spatial Relations in Images using Convolutional Neural Networks. CoRR abs/1706.04215 (2017) - [i12]Prutha Date, Ashwinkumar Ganesan, Tim Oates:
Fashioning with Networks: Neural Style Transfer to Design Clothes. CoRR abs/1707.09899 (2017) - [i11]J. T. Turner, Adam Page, Tinoosh Mohsenin, Tim Oates:
Deep Belief Networks used on High Resolution Multichannel Electroencephalography Data for Seizure Detection. CoRR abs/1708.08430 (2017) - [i10]Zhiguang Wang, Chul Gwon, Tim Oates, Adam Iezzi:
Automated Cloud Provisioning on AWS using Deep Reinforcement Learning. CoRR abs/1709.04305 (2017) - 2016
- [j20]Rémi Eyraud, Jean-Christophe Janodet, Tim Oates, Frédéric Papadopoulos:
Designing and Learning Substitutable Plane Graph Grammars. Fundam. Informaticae 146(4): 403-430 (2016) - [j19]Kavita Krishnaswamy, Ravi Kuber, Tim Oates:
Developing a limb repositioning robotic interface for persons with severe physical disabilities. Univers. Access Inf. Soc. 15(4): 609-627 (2016) - [c115]Zhiguang Wang, Tim Oates, James Lo:
Adaptive Normalized Risk-Averting Training for Deep Neural Networks. AAAI 2016: 2201-2207 - [c114]Xing Wang, Jessica Lin, Pavel Senin, Tim Oates, Sunil Gandhi, Arnold P. Boedihardjo, Crystal Chen, Susan Frankenstein:
RPM: Representative Pattern Mining for Efficient Time Series Classification. EDBT 2016: 185-196 - [c113]Nicholay Topin, Karan K. Budhraja, Tim Oates:
Feature Selection in Environments with Limited Voluntary Information Sharing. ICDM Workshops 2016: 576-583 - [c112]Bhavani Thuraisingham, Murat Kantarcioglu, Kevin W. Hamlen, Latifur Khan, Tim Finin, Anupam Joshi, Tim Oates, Elisa Bertino:
A Data Driven Approach for the Science of Cyber Security: Challenges and Directions. IRI 2016: 1-10 - [c111]Bryan Wilkinson, Tim Oates:
A Gold Standard for Scalar Adjectives. LREC 2016 - [c110]Karan K. Budhraja, Tim Oates:
Controlling Swarms by Visual Demonstration. SASO 2016: 1-10 - [c109]Hang Gao, Tim Oates:
MDSENT at SemEval-2016 Task 4: A Supervised System for Message Polarity Classification. SemEval@NAACL-HLT 2016: 139-144 - [i9]Karan Kumar Budhraja, Tim Oates:
Neuroevolution-Based Inverse Reinforcement Learning. CoRR abs/1608.02971 (2016) - [i8]Ashwinkumar Ganesan, Tim Oates, Matt Schmill:
Finding Representative Points in Multivariate Data Using PCA. CoRR abs/1610.05819 (2016) - [i7]Zhiguang Wang, Weizhong Yan, Tim Oates:
Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline. CoRR abs/1611.06455 (2016) - 2015
- [j18]Adam Page, Chris Sagedy, Emily Smith, Nasrin Attaran, Tim Oates, Tinoosh Mohsenin:
A Flexible Multichannel EEG Feature Extractor and Classifier for Seizure Detection. IEEE Trans. Circuits Syst. II Express Briefs 62-II(2): 109-113 (2015) - [c108]Sunil Gandhi, Tim Oates, Arnold P. Boedihardjo, Crystal Chen, Jessica Lin, Pavel Senin, Susan Frankenstein, Xing Wang:
A Generative Model For Time Series Discretization Based On Multiple Normal Distributions. PIKM@CIKM 2015: 19-25 - [c107]Pavel Senin, Jessica Lin, Xing Wang, Tim Oates, Sunil Gandhi, Arnold P. Boedihardjo, Crystal Chen, Susan Frankenstein:
Time series anomaly discovery with grammar-based compression. EDBT 2015: 481-492 - [c106]Adam Page, Siddharth Pramod, Tim Oates, Tinoosh Mohsenin:
An ultra low power feature extraction and classification system for wearable seizure detection. EMBC 2015: 7111-7114 - [c105]Zhiguang Wang, Tim Oates:
Pooling SAX-BoP Approaches with Boosting to Classify Multivariate Synchronous Physiological Time Series Data. FLAIRS 2015: 335-341 - [c104]Karan Kumar Budhraja, Tim Oates:
Adversarial Feature Selection. ICDM Workshops 2015: 288-294 - [c103]Zhiguang Wang, Tim Oates:
Imaging Time-Series to Improve Classification and Imputation. IJCAI 2015: 3939-3945 - [i6]Zhiguang Wang, Tim Oates:
Imaging Time-Series to Improve Classification and Imputation. CoRR abs/1506.00327 (2015) - [i5]Zhiguang Wang, Tim Oates, James Lo:
Adaptive Normalized Risk-Averting Training For Deep Neural Networks. CoRR abs/1506.02690 (2015) - [i4]Zhiguang Wang, Tim Oates:
Spatially Encoding Temporal Correlations to Classify Temporal Data Using Convolutional Neural Networks. CoRR abs/1509.07481 (2015) - 2014
- [j17]Xianshu Zhu, Tim Oates:
Finding story chains in newswire articles using random walks. Inf. Syst. Frontiers 16(5): 753-769 (2014) - [j16]Jeffrey Heinz, Colin de la Higuera, Tim Oates:
Introduction to the Special Issue on Grammatical Inference. Mach. Learn. 96(1-2): 1-3 (2014) - [c102]J. T. Turner, Adam Page, Tinoosh Mohsenin, Tim Oates:
Deep Belief Networks Used on High Resolution Multichannel Electroencephalography Data for Seizure Detection. AAAI Spring Symposia 2014 - [c101]Adam Page, J. T. Turner, Tinoosh Mohsenin, Tim Oates:
Comparing Raw Data and Feature Extraction for Seizure Detection with Deep Learning Methods. FLAIRS 2014 - [c100]Terry H. Tsai, Niels Kasch, Craig Pfeifer, Tim Oates:
Text Mining for Hypotheses and Results in Translational Medicine Studies. ICDM Workshops 2014: 127-132 - [c99]Rakesh Deivachilai, Tim Oates:
On-Line Signature Verification Using Symbolic Aggregate Approximation (SAX) and Sequential Mining Optimization (SMO). ICMLA 2014: 195-200 - [c98]Zhiguang Wang, Tim Oates:
Time Warping Symbolic Aggregation Approximation with Bag-of-Patterns Representation for Time Series Classification. ICMLA 2014: 270-275 - [c97]Pavel Senin, Jessica Lin, Xing Wang, Tim Oates, Sunil Gandhi, Arnold P. Boedihardjo, Crystal Chen, Susan Frankenstein, Manfred Lerner:
GrammarViz 2.0: A Tool for Grammar-Based Pattern Discovery in Time Series. ECML/PKDD (3) 2014: 468-472 - 2013
- [c96]Tim Oates, Arnold P. Boedihardjo, Jessica Lin, Crystal Chen, Susan Frankenstein, Sunil Gandhi:
Motif discovery in spatial trajectories using grammar inference. CIKM 2013: 1465-1468 - [c95]Adrian Rosebrock, Tim Oates, Jesus J. Caban:
Ecosembles: A Rapidly Deployable Image Classification System Using Feature-Views. ICMLA (1) 2013: 1-8 - [c94]Tongchun Du, Michael T. Cox, Don Perlis, Jared Shamwell, Tim Oates:
From Robots to Reinforcement Learning. ICTAI 2013: 540-545 - [c93]Paul McNamee, James Mayfield, Tim Finin, Tim Oates, Dawn J. Lawrie, Tan Xu, Douglas W. Oard:
KELVIN: a tool for automated knowledge base construction. HLT-NAACL 2013: 32-35 - [c92]Xianshu Zhu, Tim Oates:
Finding news story chains based on multi-dimensional event profiles. OAIR 2013: 157-164 - [i3]