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ORCIDAlexander G. Gray
Alexander Gray 0001
Person information
- affiliation: Centaur AI Institute, USA
- affiliation (former): IBM Research, Yorktown Heights, NY, USA
- affiliation (former): College of Computing, Georgia Institute of Technology
Other persons with the same name
- Alexander Gray — disambiguation page
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2020 – today
- 2025
[c83]Stephen Carrow, Kyle Erwin, Olga Vilenskaia, Parikshit Ram, Tim Klinger, Naweed Khan, Ndivhuwo Makondo, Alexander G. Gray:
Neural Reasoning Networks: Efficient Interpretable Neural Networks with Automatic Textual Explanations. AAAI 2025: 15669-15677- [i51]Luis A. Lastras, Barry M. Trager, Jonathan Lenchner, Wojciech Szpankowski, Chai Wah Wu, Mark S. Squillante, Alexander Gray:
Breaking through the classical Shannon entropy limit: A new frontier through logical semantics. CoRR abs/2501.00612 (2025) - [i50]Kyle Erwin, Guy Axelrod, Maria Chang, Achille Fokoue, Maxwell Crouse, Soham Dan, Tian Gao, Rosario Uceda-Sosa, Ndivhuwo Makondo, Naweed Khan, Alexander G. Gray:
Few-shot Policy (de)composition in Conversational Question Answering. CoRR abs/2501.11335 (2025) - [i49]Bowen Li, Tom Silver, Sebastian A. Scherer, Alexander G. Gray:
Bilevel Learning for Bilevel Planning. CoRR abs/2502.08697 (2025) - 2024
- [j12]Fábio G. Cozman
, Radu Marinescu, Junkyu Lee, Alexander G. Gray, Ryan Riegel, Debarun Bhattacharjya:
Markov conditions and factorization in logical credal networks. Int. J. Approx. Reason. 172: 109237 (2024) - [c82]Parikshit Ram, Tim Klinger, Alexander G. Gray:
What Makes Models Compositional? A Theoretical View. IJCAI 2024: 4824-4832 - [c81]Parikshit Ram, Tim Klinger, Alexander G. Gray:
What makes Models Compositional? A Neuro-Symbolic Theoretical View (Extended Abstract). LNSAI@IJCAI 2024 - [c80]Radu Marinescu, Junkyu Lee, Debarun Bhattacharjya, Fábio G. Cozman, Alexander G. Gray:
Abductive Reasoning in Logical Credal Networks. NeurIPS 2024 - [c79]Bowen Li, Zhaoyu Li, Qiwei Du, Jinqi Luo, Wenshan Wang, Yaqi Xie, Simon Stepputtis, Chen Wang, Katia P. Sycara, Pradeep Ravikumar, Alexander G. Gray, Xujie Si, Sebastian A. Scherer:
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation. NeurIPS 2024 - [i48]Chitra Subramanian, Miao Liu, Naweed Khan, Jonathan Lenchner, Aporva Amarnath, Sarathkrishna Swaminathan, Ryan Riegel, Alexander Gray:
A Neuro-Symbolic Approach to Multi-Agent RL for Interpretability and Probabilistic Decision Making. CoRR abs/2402.13440 (2024) - [i47]Parikshit Ram, Tim Klinger, Alexander G. Gray:
What makes Models Compositional? A Theoretical View: With Supplement. CoRR abs/2405.02350 (2024) - [i46]Stephen Carrow, Kyle Harper Erwin, Olga Vilenskaia, Parikshit Ram, Tim Klinger, Naweed Aghmad Khan, Ndivhuwo Makondo, Alexander Gray:
Neural Reasoning Networks: Efficient Interpretable Neural Networks With Automatic Textual Explanations. CoRR abs/2410.07966 (2024) - [i45]Bowen Li, Zhaoyu Li, Qiwei Du, Jinqi Luo, Wenshan Wang, Yaqi Xie, Simon Stepputtis, Chen Wang, Katia P. Sycara, Pradeep Kumar Ravikumar, Alexander G. Gray, Xujie Si, Sebastian A. Scherer:
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation. CoRR abs/2411.00773 (2024) - 2023
- [c78]Don Joven Agravante, Daiki Kimura, Michiaki Tatsubori, Asim Munawar, Alexander Gray:
Learning Neuro-Symbolic World Models with Conversational Proprioception. ACL (2) 2023: 648-656 - [c77]Keerthiram Murugesan, Sarathkrishna Swaminathan, Soham Dan, Subhajit Chaudhury, R. Chulaka Gunasekara, Maxwell Crouse, Diwakar Mahajan, Ibrahim Abdelaziz, Achille Fokoue, Pavan Kapanipathi, Salim Roukos, Alexander Gray:
MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types. ACL (Findings) 2023: 4485-4503 - [c76]Subhajit Chaudhury, Sarathkrishna Swaminathan, Daiki Kimura, Prithviraj Sen, Keerthiram Murugesan, Rosario Uceda-Sosa, Michiaki Tatsubori, Achille Fokoue, Pavan Kapanipathi, Asim Munawar, Alexander Gray:
Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning. ACL (1) 2023: 6764-6776 - [c75]Shajith Ikbal, Udit Sharma, Hima Karanam, Sumit Neelam, Ronny Luss, Dheeraj Sreedhar, Pavan Kapanipathi, Naweed Khan, Kyle Erwin, Ndivhuwo Makondo, Ibrahim Abdelaziz, Achille Fokoue, Alexander Gray, Maxwell Crouse, Subhajit Chaudhury, Chitra Subramanian:
Self-Supervised Rule Learning to Link Text Segments to Relational Elements of Structured Knowledge. EMNLP (Findings) 2023: 1707-1718 - [c74]Radu Marinescu, Haifeng Qian, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel:
Approximate Inference in Logical Credal Networks. IJCAI 2023: 5694-5701 - [c73]Radu Marinescu, Debarun Bhattacharjya, Junkyu Lee, Fábio G. Cozman, Alexander G. Gray:
Credal Marginal MAP. NeurIPS 2023 - [c72]Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble:
Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection. SDM 2023: 802-810 - [i44]Parikshit Ram, Alexander G. Gray, Horst C. Samulowitz, Gregory Bramble:
Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection. CoRR abs/2301.05131 (2023) - [i43]Luis A. Lastras, Barry M. Trager, Jonathan Lenchner, Wojciech Szpankowski, Chai Wah Wu, Mark S. Squillante, Alexander Gray:
Towards a Unification of Logic and Information Theory. CoRR abs/2301.10414 (2023) - [i42]Maxwell Crouse, Ramón Fernandez Astudillo, Tahira Naseem, Subhajit Chaudhury, Pavan Kapanipathi, Salim Roukos, Alexander Gray:
Scalable Learning of Latent Language Structure With Logical Offline Cycle Consistency. CoRR abs/2305.20018 (2023) - [i41]Keerthiram Murugesan, Sarathkrishna Swaminathan, Soham Dan, Subhajit Chaudhury, R. Chulaka Gunasekara, Maxwell Crouse, Diwakar Mahajan, Ibrahim Abdelaziz, Achille Fokoue, Pavan Kapanipathi, Salim Roukos, Alexander Gray:
MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types. CoRR abs/2306.10452 (2023) - [i40]Subhajit Chaudhury, Sarathkrishna Swaminathan, Daiki Kimura, Prithviraj Sen, Keerthiram Murugesan, Rosario Uceda-Sosa, Michiaki Tatsubori, Achille Fokoue, Pavan Kapanipathi, Asim Munawar, Alexander Gray:
Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning. CoRR abs/2307.02689 (2023) - [i39]Tim Klinger, Luke Liu, Soham Dan, Maxwell Crouse, Parikshit Ram, Alexander Gray:
Compositional Program Generation for Systematic Generalization. CoRR abs/2309.16467 (2023) - 2022
- [c71]Prithviraj Sen, Breno W. S. R. de Carvalho, Ryan Riegel, Alexander G. Gray:
Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks. AAAI 2022: 8212-8219 - [c70]Prithviraj Sen, Breno W. S. R. de Carvalho, Ibrahim Abdelaziz, Pavan Kapanipathi, Salim Roukos, Alexander G. Gray:
Logical Neural Networks for Knowledge Base Completion with Embeddings & Rules. EMNLP 2022: 3863-3875 - [c69]Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam:
SYGMA: A System for Generalizable and Modular Question Answering Over Knowledge Bases. EMNLP (Findings) 2022: 3866-3879 - [c68]Subhajit Chaudhury, Sarathkrishna Swaminathan, R. Chulaka Gunasekara, Maxwell Crouse, Srinivas Ravishankar, Daiki Kimura, Keerthiram Murugesan, Ramón Fernandez Astudillo, Tahira Naseem, Pavan Kapanipathi, Alexander Gray:
X-FACTOR: A Cross-metric Evaluation of Factual Correctness in Abstractive Summarization. EMNLP 2022: 7100-7110 - [c67]G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Saswati Dana, Dinesh Garg, Pavan Kapanipathi, Salim Roukos, Alexander G. Gray, L. Venkata Subramaniam:
Zero-shot Entity Linking with Less Data. NAACL-HLT (Findings) 2022: 1681-1697 - [c66]Radu Marinescu, Haifeng Qian, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel, Pravinda Sahu:
Logical Credal Networks. NeurIPS 2022 - [i38]Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander G. Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam:
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases. CoRR abs/2201.05793 (2022) - 2021
- [c65]Ibrahim Abdelaziz, Srinivas Ravishankar, Pavan Kapanipathi, Salim Roukos, Alexander G. Gray:
A Semantic Parsing and Reasoning-Based Approach to Knowledge Base Question Answering. AAAI 2021: 15985-15987 - [c64]Daiki Kimura, Subhajit Chaudhury, Masaki Ono, Michiaki Tatsubori, Don Joven Agravante, Asim Munawar, Akifumi Wachi, Ryosuke Kohita, Alexander Gray:
LOA: Logical Optimal Actions for Text-based Interaction Games. ACL (demo) 2021: 227-231 - [c63]Tahira Naseem, Srinivas Ravishankar, Nandana Mihindukulasooriya, Ibrahim Abdelaziz, Young-Suk Lee, Pavan Kapanipathi, Salim Roukos, Alfio Gliozzo, Alexander G. Gray:
A Semantics-aware Transformer Model of Relation Linking for Knowledge Base Question Answering. ACL/IJCNLP (2) 2021: 256-262 - [c62]Hang Jiang, Sairam Gurajada, Qiuhao Lu, Sumit Neelam, Lucian Popa, Prithviraj Sen, Yunyao Li, Alexander G. Gray:
LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking. ACL/IJCNLP (1) 2021: 775-787 - [c61]Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander G. Gray, Ramón Fernandez Astudillo, Maria Chang, Cristina Cornelio, Saswati Dana, Achille Fokoue, Dinesh Garg, Alfio Gliozzo, Sairam Gurajada, Hima Karanam, Naweed Khan, Dinesh Khandelwal, Young-Suk Lee, Yunyao Li, Francois P. S. Luus, Ndivhuwo Makondo, Nandana Mihindukulasooriya, Tahira Naseem, Sumit Neelam, Lucian Popa, Revanth Gangi Reddy, Ryan Riegel, Gaetano Rossiello, Udit Sharma, G. P. Shrivatsa Bhargav, Mo Yu:
Leveraging Abstract Meaning Representation for Knowledge Base Question Answering. ACL/IJCNLP (Findings) 2021: 3884-3894 - [c60]Daiki Kimura, Masaki Ono, Subhajit Chaudhury, Ryosuke Kohita, Akifumi Wachi, Don Joven Agravante, Michiaki Tatsubori, Asim Munawar, Alexander Gray:
Neuro-Symbolic Reinforcement Learning with First-Order Logic. EMNLP (1) 2021: 3505-3511 - [c59]Songtao Lu, Naweed Khan, Ismail Yunus Akhalwaya, Ryan Riegel, Lior Horesh, Alexander G. Gray:
Training Logical Neural Networks by Primal-Dual Methods for Neuro-Symbolic Reasoning. ICASSP 2021: 5559-5563 - [i37]Francois P. S. Luus, Prithviraj Sen, Pavan Kapanipathi, Ryan Riegel, Ndivhuwo Makondo, Thabang Lebese, Alexander G. Gray:
Logic Embeddings for Complex Query Answering. CoRR abs/2103.00418 (2021) - [i36]Daiki Kimura, Subhajit Chaudhury, Akifumi Wachi, Ryosuke Kohita, Asim Munawar, Michiaki Tatsubori, Alexander Gray:
Reinforcement Learning with External Knowledge by using Logical Neural Networks. CoRR abs/2103.02363 (2021) - [i35]Hang Jiang, Sairam Gurajada, Qiuhao Lu, Sumit Neelam, Lucian Popa, Prithviraj Sen, Yunyao Li, Alexander G. Gray:
LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking. CoRR abs/2106.09795 (2021) - [i34]Prithviraj Sen, Breno W. S. R. Carvalho, Ibrahim Abdelaziz, Pavan Kapanipathi, Francois P. S. Luus, Salim Roukos, Alexander G. Gray:
Combining Rules and Embeddings via Neuro-Symbolic AI for Knowledge Base Completion. CoRR abs/2109.09566 (2021) - [i33]Haifeng Qian, Radu Marinescu, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel, Pravinda Sahu:
Logical Credal Networks. CoRR abs/2109.12240 (2021) - [i32]Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander G. Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam:
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases. CoRR abs/2109.13430 (2021) - [i31]Daiki Kimura, Masaki Ono, Subhajit Chaudhury, Ryosuke Kohita, Akifumi Wachi, Don Joven Agravante, Michiaki Tatsubori, Asim Munawar, Alexander Gray:
Neuro-Symbolic Reinforcement Learning with First-Order Logic. CoRR abs/2110.10963 (2021) - [i30]Daiki Kimura, Subhajit Chaudhury, Masaki Ono, Michiaki Tatsubori, Don Joven Agravante, Asim Munawar, Akifumi Wachi, Ryosuke Kohita, Alexander Gray:
LOA: Logical Optimal Actions for Text-based Interaction Games. CoRR abs/2110.10973 (2021) - [i29]Prithviraj Sen, Breno W. S. R. de Carvalho, Ryan Riegel, Alexander G. Gray:
Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks. CoRR abs/2112.03324 (2021) - 2020
- [c58]Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Dakuo Wang, Andrew Conn, Alexander G. Gray:
An ADMM Based Framework for AutoML Pipeline Configuration. AAAI 2020: 4892-4899 - [c57]Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray:
Survey on Automated End-to-End Data Science? IJCNN 2020: 1-9 - [c56]Daniel Karl I. Weidele, Justin D. Weisz, Erick Oduor, Michael J. Muller, Josh Andres, Alexander G. Gray, Dakuo Wang:
AutoAIViz: opening the blackbox of automated artificial intelligence with conditional parallel coordinates. IUI 2020: 308-312 - [c55]Nandana Mihindukulasooriya, Gaetano Rossiello, Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Mo Yu, Alfio Gliozzo, Salim Roukos, Alexander G. Gray:
Leveraging Semantic Parsing for Relation Linking over Knowledge Bases. ISWC (1) 2020: 402-419 - [i28]Parikshit Ram, Sijia Liu, Deepak Vijaykeerthy, Dakuo Wang, Djallel Bouneffouf, Gregory Bramble, Horst Samulowitz, Alexander G. Gray:
Solving Constrained CASH Problems with ADMM. CoRR abs/2006.09635 (2020) - [i27]Ryan Riegel, Alexander G. Gray, Francois P. S. Luus, Naweed Khan, Ndivhuwo Makondo, Ismail Yunus Akhalwaya, Haifeng Qian, Ronald Fagin, Francisco Barahona, Udit Sharma, Shajith Ikbal, Hima Karanam, Sumit Neelam, Ankita Likhyani, Santosh K. Srivastava:
Logical Neural Networks. CoRR abs/2006.13155 (2020) - [i26]Ronald Fagin, Ryan Riegel, Alexander G. Gray:
Foundations of Reasoning with Uncertainty via Real-valued Logics. CoRR abs/2008.02429 (2020) - [i25]Nandana Mihindukulasooriya, Gaetano Rossiello, Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Mo Yu, Alfio Gliozzo, Salim Roukos, Alexander G. Gray:
Leveraging Semantic Parsing for Relation Linking over Knowledge Bases. CoRR abs/2009.07726 (2020) - [i24]Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander G. Gray, Ramón Fernandez Astudillo, Maria Chang, Cristina Cornelio, Saswati Dana, Achille Fokoue, Dinesh Garg, Alfio Gliozzo, Sairam Gurajada, Hima Karanam, Naweed Khan, Dinesh Khandelwal, Young-Suk Lee, Yunyao Li, Francois P. S. Luus, Ndivhuwo Makondo, Nandana Mihindukulasooriya, Tahira Naseem, Sumit Neelam, Lucian Popa, Revanth Gangi Reddy, Ryan Riegel, Gaetano Rossiello, Udit Sharma, G. P. Shrivatsa Bhargav, Mo Yu:
Question Answering over Knowledge Bases by Leveraging Semantic Parsing and Neuro-Symbolic Reasoning. CoRR abs/2012.01707 (2020)
2010 – 2019
- 2019
- [j11]Dakuo Wang, Justin D. Weisz, Michael J. Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla R. Tausczik, Horst Samulowitz, Alexander G. Gray:
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI. Proc. ACM Hum. Comput. Interact. 3(CSCW): 211:1-211:24 (2019) - [i23]Sijia Liu, Parikshit Ram, Djallel Bouneffouf, Gregory Bramble, Andrew R. Conn, Horst Samulowitz, Alexander G. Gray:
Automated Machine Learning via ADMM. CoRR abs/1905.00424 (2019) - [i22]Dakuo Wang, Justin D. Weisz, Michael J. Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla R. Tausczik, Horst Samulowitz, Alexander G. Gray:
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI. CoRR abs/1909.02309 (2019) - [i21]Charu C. Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray:
How can AI Automate End-to-End Data Science? CoRR abs/1910.14436 (2019) - [i20]Daniel Karl I. Weidele, Justin D. Weisz, Eno Oduor, Michael J. Muller, Josh Andres, Alexander G. Gray, Dakuo Wang:
AutoAIViz: Opening the Blackbox of Automated Artificial Intelligence with Conditional Parallel Coordinates. CoRR abs/1912.06723 (2019) - 2017
- [c54]Parikshit Ram, Alexander G. Gray:
Fraud Detection with Density Estimation Trees. ADF@KDD 2017: 85-94 - 2014
- [j10]Dongryeol Lee, Piyush Sao, Richard W. Vuduc, Alexander G. Gray:
A distributed kernel summation framework for general-dimension machine learning. Stat. Anal. Data Min. 7(1): 1-13 (2014) - 2013
- [j9]Wei Guan, Alexander G. Gray:
Sparse high-dimensional fractional-norm support vector machine via DC programming. Comput. Stat. Data Anal. 67: 136-148 (2013) - [j8]Kichun Lee, Alexander G. Gray, Heeyoung Kim:
Dependence maps, a dimensionality reduction with dependence distance for high-dimensional data. Data Min. Knowl. Discov. 26(3): 512-532 (2013) - [j7]Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray:
MLPACK: a scalable C++ machine learning library. J. Mach. Learn. Res. 14(1): 801-805 (2013) - [c53]Nishant Ajay Mehta, Alexander G. Gray:
Sparsity-Based Generalization Bounds for Predictive Sparse Coding. ICML (1) 2013: 36-44 - [c52]Hua Ouyang, Niao He, Long Q. Tran, Alexander G. Gray:
Stochastic Alternating Direction Method of Multipliers. ICML (1) 2013: 80-88 - [c51]Ryan R. Curtin, William B. March, Parikshit Ram, David V. Anderson, Alexander G. Gray, Charles L. Isbell Jr.:
Tree-Independent Dual-Tree Algorithms. ICML (3) 2013: 1435-1443 - [c50]Parikshit Ram, Alexander G. Gray:
Which Space Partitioning Tree to Use for Search? NIPS 2013: 656-664 - [c49]Ryan R. Curtin, Alexander G. Gray, Parikshit Ram:
Fast Exact Max-Kernel Search. SDM 2013: 1-9 - [c48]Alexander G. Gray, Hassan A. Kingravi, Patricio A. Vela:
Reduced Set KPCA for Improving the Training and Execution Speed of Kernel Machines. SDM 2013: 441-449 - [c47]Ravi Ganti, Alexander G. Gray:
Building Bridges: Viewing Active Learning from the Multi-Armed Bandit Lens. UAI 2013 - [i19]Ryan R. Curtin, William B. March, Parikshit Ram, David V. Anderson, Alexander G. Gray, Charles Lee Isbell Jr.:
Tree-Independent Dual-Tree Algorithms. CoRR abs/1304.4327 (2013) - [i18]Ravi Ganti, Alexander G. Gray:
Local Support Vector Machines: Formulation and Analysis. CoRR abs/1309.3699 (2013) - [i17]Ravi Ganti, Alexander G. Gray:
Building Bridges: Viewing Active Learning from the Multi-Armed Bandit Lens. CoRR abs/1309.6830 (2013) - 2012
- [j6]Jacqueline Fairley, George K. Georgoulas, Nishant A. Mehta, Alexander G. Gray, Donald L. Bliwise:
Computer detection approaches for the identification of phasic electromyographic (EMG) activity during human sleep. Biomed. Signal Process. Control. 7(6): 606-615 (2012) - [j5]Dongryeol Lee, Arkadas Ozakin, Alexander G. Gray:
Multibody multipole methods. J. Comput. Phys. 231(20): 6827-6845 (2012) - [c46]Jacob VanderPlas, Andrew J. Connolly, Zeljko Ivezic, Alexander G. Gray:
Introduction to astroML: Machine learning for astrophysics. CIDU 2012: 47-54 - [c45]Hua Ouyang, Alexander G. Gray:
Stochastic Smoothing for Nonsmooth Minimizations: Accelerating SGD by Exploiting Structure. ICML 2012 - [c44]Hua Ouyang, Alexander G. Gray:
NASA: achieving lower regrets and faster rates via adaptive stepsizes. KDD 2012: 159-167 - [c43]Parikshit Ram, Alexander G. Gray:
Maximum inner-product search using cone trees. KDD 2012: 931-939 - [c42]William B. March, Andrew J. Connolly, Alexander G. Gray:
Fast algorithms for comprehensive n-point correlation estimates. KDD 2012: 1478-1486 - [c41]Nishant A. Mehta, Dongryeol Lee, Alexander G. Gray:
Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL. NIPS 2012: 2159-2167 - [c40]Sooraj Bhat, Ashish Agarwal, Richard W. Vuduc, Alexander G. Gray:
A type theory for probability density functions. POPL 2012: 545-556 - [c39]William B. March, Kenneth Czechowski, Marat Dukhan, Thomas Benson, Dongryeol Lee, Andrew J. Connolly, Richard W. Vuduc, Edmond Chow, Alexander G. Gray:
Optimizing the computation of n-point correlations on large-scale astronomical data. SC 2012: 74 - [c38]Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray:
A Distributed Kernel Summation Framework for General-Dimension Machine Learning. SDM 2012: 391-402 - [c37]Parikshit Ram, Dongryeol Lee, Alexander G. Gray:
Nearest-Neighbor Search on a Time Budget via Max-Margin Trees. SDM 2012: 1011-1022 - [c36]Ravi Ganti, Alexander G. Gray:
UPAL: Unbiased Pool Based Active Learning. AISTATS 2012: 422-431 - [i16]Nishant A. Mehta, Alexander G. Gray:
On the Sample Complexity of Predictive Sparse Coding. CoRR abs/1202.4050 (2012) - [i15]Parikshit Ram, Alexander G. Gray:
Maximum Inner-Product Search using Tree Data-structures. CoRR abs/1202.6101 (2012) - [i14]Hua Ouyang, Alexander G. Gray:
Stochastic Smoothing for Nonsmooth Minimizations: Accelerating SGD by Exploiting Structure. CoRR abs/1205.4481 (2012) - [i13]Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.:
Fast Nonparametric Conditional Density Estimation. CoRR abs/1206.5278 (2012) - [i12]Dongryeol Lee, Alexander G. Gray:
Faster Gaussian Summation: Theory and Experiment. CoRR abs/1206.6857 (2012) - [i11]Nishant A. Mehta, Dongryeol Lee, Alexander G. Gray:
Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL. CoRR abs/1209.2784 (2012) - [i10]Ryan R. Curtin, Parikshit Ram, Alexander G. Gray:
Fast Exact Max-Kernel Search. CoRR abs/1210.6287 (2012) - [i9]Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray:
MLPACK: A Scalable C++ Machine Learning Library. CoRR abs/1210.6293 (2012) - [i8]Hua Ouyang, Niao He, Alexander G. Gray:
Stochastic ADMM for Nonsmooth Optimization. CoRR abs/1211.0632 (2012) - 2011
- [c35]Wei Guan, Arkadas Ozakin, Alexander G. Gray, Jose Borreguero, Shashi Bhushan Pandit, Anna Jagielska, Liliana Wroblewska, Jeffrey Skolnick:
Learning Protein Folding Energy Functions. ICDM 2011: 1062-1067 - [c34]Parikshit Ram, Alexander G. Gray:
Density estimation trees. KDD 2011: 627-635 - [c33]Ailar Javadi, Alexander Gray, David Anderson, Visar Berisha:
Semi-supervised hierarchy learning using multiple-labeled data. MLSP 2011: 1-6 - [c32]Ravi Sastry Ganti Mahapatruni, Alexander G. Gray:
CAKE: Convex Adaptive Kernel Density Estimation. AISTATS 2011: 498-506 - [i7]Dongryeol Lee, Alexander G. Gray, Andrew W. Moore:
Dual-Tree Fast Gauss Transforms. CoRR abs/1102.2878 (2011) - [i6]Hua Ouyang, Alexander G. Gray:
Data-Distributed Weighted Majority and Online Mirror Descent. CoRR abs/1105.2274 (2011) - [i5]Dongryeol Lee, Arkadas Ozakin, Alexander G. Gray:
Multibody Multipole Methods. CoRR abs/1105.2769 (2011) - [i4]Ravi Ganti, Alexander G. Gray:
UPAL: Unbiased Pool Based Active Learning. CoRR abs/1111.1784 (2011) - 2010
- [j4]Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.:
Fast kernel conditional density estimation: A dual-tree Monte Carlo approach. Comput. Stat. Data Anal. 54(7): 1707-1718 (2010) - [c31]Hua Ouyang, Alexander G. Gray:
Stochastic Mirror Descent Algorithm for L1-Regularized Risk Minimizations. CIT 2010: 1241-1245 - [c30]William B. March, Parikshit Ram, Alexander G. Gray:
Fast euclidean minimum spanning tree: algorithm, analysis, and applications. KDD 2010: 603-612 - [c29]Ashish Agarwal, Sooraj Bhat, Alexander G. Gray, Ignacio E. Grossmann:
Automating Mathematical Program Transformations. PADL 2010: 134-148 - [c28]Hua Ouyang, Alexander G. Gray:
Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs. SDM 2010: 245-256 - [c27]Sooraj Bhat, Ashish Agarwal, Alexander G. Gray, Richard W. Vuduc:
Toward interactive statistical modeling. ICCS 2010: 1835-1844 - [i3]Nishant A. Mehta, Alexander G. Gray:
Generative and Latent Mean Map Kernels. CoRR abs/1005.0188 (2010)
2000 – 2009
- 2009
- [j3]Wei Guan, Manshui Zhou, Christina Y. Hampton, Benedict B. Benigno, L. DeEtte Walker, Alexander G. Gray, John F. McDonald, Facundo M. Fernández:
Ovarian cancer detection from metabolomic liquid chromatography/mass spectrometry data by support vector machines. BMC Bioinform. 10: 259 (2009) - [j2]Rajesh Narasimha, Hua Ouyang, Alexander G. Gray, Steven W. McLaughlin, Sriram Subramaniam:
Automatic joint classification and segmentation of whole cell 3D images. Pattern Recognit. 42(6): 1067-1079 (2009) - [c26]Arkadas Ozakin, Alexander G. Gray:
Submanifold density estimation. NIPS 2009: 1375-1382 - [c25]Parikshit Ram, Dongryeol Lee, William B. March, Alexander G. Gray:
Linear-time Algorithms for Pairwise Statistical Problems. NIPS 2009: 1527-1535 - [c24]Parikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander G. Gray:
Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions. NIPS 2009: 1536-1544 - [c23]Nishant A. Mehta, Alexander G. Gray:
FuncICA for Time Series Pattern Discovery. SDM 2009: 73-84 - [c22]Nikolaos Vasiloglou, Alexander G. Gray, David V. Anderson:
Non-negative Matrix Factorization, Convexity and Isometry. SDM 2009: 673-684 - [c21]Shuang Hao, Nadeem Ahmed Syed, Nick Feamster, Alexander G. Gray, Sven Krasser:
Detecting Spammers with SNARE: Spatio-temporal Network-level Automatic Reputation Engine. USENIX Security Symposium 2009: 101-118 - 2008
- [c20]Hua Ouyang, Alexander G. Gray:
Learning dissimilarities by ranking: from SDP to QP. ICML 2008: 728-735 - [c19]Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.:
QUIC-SVD: Fast SVD Using Cosine Trees. NIPS 2008: 673-680 - [c18]Dongryeol Lee, Alexander G. Gray:
Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method. NIPS 2008: 929-936 - [c17]Ryan Riegel, Alexander G. Gray, Gordon Richards:
Massive-Scale Kernel Discriminant Analysis: Mining for Quasars. SDM 2008: 208-218 - [c16]Nick Feamster, Alexander G. Gray:
Can great research be taught?: independent research with cross-disciplinary thinking and broader impact. SIGCSE 2008: 471-475 - [i2]Nikolaos Vasiloglou, Alexander G. Gray, David V. Anderson:
Non-Negative Matrix Factorization, Convexity and Isometry. CoRR abs/0810.2311 (2008) - [i1]Nikolaos Vasiloglou, Alexander G. Gray, David V. Anderson:
Learning Isometric Separation Maps. CoRR abs/0810.4611 (2008) - 2007
- [c15]Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell Jr.:
Ultrafast Monte Carlo for Statistical Summations. NIPS 2007: 673-680 - [c14]Michael P. Holmes, Alexander G. Gray, Charles L. Isbell Jr.:
Fast Nonparametric Conditional Density Estimation. UAI 2007: 175-182 - [c13]Ping Wang, Dongryeol Lee, Alexander G. Gray, James M. Rehg:
Fast Mean Shift with Accurate and Stable Convergence. AISTATS 2007: 604-611 - 2006
- [j1]Ting Liu, Andrew W. Moore, Alexander G. Gray:
New Algorithms for Efficient High-Dimensional Nonparametric Classification. J. Mach. Learn. Res. 7: 1135-1158 (2006) - [c12]George K. Baah, Alexander G. Gray, Mary Jean Harrold:
On-line anomaly detection of deployed software: a statistical machine learning approach. SOQUA 2006: 70-77 - [c11]Dongryeol Lee, Alexander G. Gray:
Faster Gaussian Summation: Theory and Experiment. UAI 2006 - 2005
- [c10]Dongryeol Lee, Alexander G. Gray, Andrew W. Moore:
Dual-Tree Fast Gauss Transforms. NIPS 2005: 747-754 - 2004
- [c9]Ting Liu, Andrew W. Moore, Alexander G. Gray, Ke Yang:
An Investigation of Practical Approximate Nearest Neighbor Algorithms. NIPS 2004: 825-832 - 2003
- [c8]Alexander G. Gray, Andrew W. Moore:
Rapid Evaluation of Multiple Density Models. AISTATS 2003: 117-123 - [c7]Ting Liu, Andrew W. Moore, Alexander G. Gray:
New Algorithms for Efficient High Dimensional Non-parametric Classification. NIPS 2003: 265-272 - [c6]Alexander G. Gray, Andrew W. Moore:
Nonparametric Density Estimation: Toward Computational Tractability. SDM 2003: 203-211 - 2002
- [c5]Alexander G. Gray, Bernd Fischer, Johann Schumann, Wray L. Buntine:
Automatic Derivation of Statistical Algorithms: The EM Family and Beyond. NIPS 2002: 673-680 - 2000
- [c4]Alexander G. Gray, Andrew W. Moore:
'N-Body' Problems in Statistical Learning. NIPS 2000: 521-527
1990 – 1999
- 1999
- [c3]Tara A. Estlin, Alexander G. Gray, Tobias Mann, Gregg R. Rabideau, Rebecca Castaño, Steve A. Chien, Eric Mjolsness:
An Integrated System for Multi-Rover Scientific Exploration. AAAI/IAAI 1999: 613-620 - 1998
- [c2]Colin P. Williams, Alexander G. Gray:
Automated Design of Quantum Circuits. QCQC 1998: 113-125 - 1995
- [c1]Padhraic Smyth, Alexander G. Gray, Usama M. Fayyad:
Retrofitting Decision Tree Classifiers Using Kernel Density Estimation. ICML 1995: 506-514
Coauthor Index
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