Machine Learning

Publications

Books    
Technical Reports
 

• Contextual Grounding of Natural Language Phrases in Images

  NeurIPS 2019 workshop on Visually Grounded Interaction and Language (ViGIL)
  pp. 1-6, 2019

  Farley Lai, Ning Xie, Derek Doran, Asim Kadav
  12/13/2019

• On Novel Object Recognition: A Unified Framework for Discriminability and Adaptability

  CIKM 2019
  pp. 2265-2268, 2019

  Kai Li , Martin Renqiang Min, Bing Bai, Hans Peter Graf, Yun Fu
  11/04/2019

• Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective

  ICCV 2019
  pp. 3583-3592, 2019

  Kai Li , Martin Renqiang Min, Yun Fu
  10/27/2019

• Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis

  IJCAI 2019
  pp.1997-2001, 2019

  Yogesh Balaji, Martin Renqiang Min, Bing Bai, Rama Chellappa, Hans Peter Graf
  08/10/2019

• Learning K-way D-dimensional Discrete Embedding for Hierarchical Data Visualization and Retrieval

  IJCAI 2019
  pp. 2966-2972, 2019

  Xiaoyuan Liang , Martin Renqiang Min, Hongyu Guo, Guiling Wang
  08/10/2019

• Tripping through time: Efficient Temporal Localization of Activities in Videos

  CVPR 2019
  pp. 1-7, 2019

  Meera Hahn, Asim Kadav, James M. Rehg, Hans Peter Graf
  05/16/2019

• A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction

  SDM 2019
  pp. 100-108, 2019

  Xiaoyuan Liang, Guiling Wang, Martin Renqiang Min, Yi Qi, Zhu Han
  05/02/2019

• Visual Entailment Task for Visually-Grounded Language Learning

  NeurIPS 2018 workshop on Visually Grounded Interaction and Language (ViGIL)
  pp. 1-7, 2018

  Ning Xie, Farley Lai, Derek Doran, Asim Kadav
  12/07/2018

• Leveraging Knowledge Bases for Future Prediction with Memory Comparison Networks

  AI Communications
  31(6):465-483, 2018

  Daniel Andrade, Bing Bai, Ramkumar Rajendrany, Yotaro Watanabe
  11/15/2018

• Teaching Syntax by Adversarial Distraction

  EMNLP 2018
  pp. 79-84, 2018

  Juho Kim, Christopher Malon, Asim Kadav
  10/31/2018

• Learning Context-Aware Convolutional Filters for Text Processing

  EMNLP 2018
  pp. 1839-1848, 2018

  Dinghan Shen, Martin Renqiang Min, Yitong Li, Lawrence Carin
  10/31/2018

• Team Papelo: Transformer Networks at FEVER

  EMNLP 2018
  pp. 109-113, 2018

  Christopher Malon
  10/31/2018

• Parametric t-Distributed Stochastic Exemplar-centered Embedding

  ECML 2018
  pp. 1-16, 2018

  Dinghan Shen, Martin Renqiang Min, Hongyu Guo
  09/10/2018

• DeepConf: Automating Data Center Network Topologies Management with Machine Learning

  ACM SIGCOMM 2018 Workshop on Network Meets AI & ML (NetAI 2018)
  pp. 1-7, 2018

  Saim Salman, Christopher Streiffer, Huan Chen, Theophilus Benson, Asim Kadav
  08/24/2018

• Baseline Needs More Love: On SimpleWord-Embedding-Based Models and Associated Pooling Mechanisms

  ACL 2018
  pp. 440-450, 2018

  Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin
  07/15/2018

• Learning K-way D-dimensional Discrete Code For Compact Embedding Representations

  ICML 2018
  pp. 1-10, 2018

  Ting Chen, Martin Renqiang Min, Yizhou Sun
  07/10/2018

• Attend and Interact: Higher-Order Object Interactions for Video Understanding

  CVPR 2018
  6790-6800, 2018

  Chih-Yao Ma, Asim Kadav, Iain Melvin, Zsolt Kira, Ghassan AlRegib, Hans Peter Graf
  06/18/2018

• Adaptive Memory Networks

  ICLR 2018
  pp. 1-13, 2018

  Daniel Li, Asim Kadav
  04/30/2018

• Adaptive Feature Abstraction for Translating Video to Text

  The Thirty-Second AAAI Conference on Artificial Intelligence
  pp 1-13, 2018

  Yunchen Pu, Martin Renqiang Min
  02/02/2018

• Video Generation From Text

  The Thirty-Second AAAI Conference on Artificial Intelligence
  pp. 1-8, 2018

  Yitong Li, Martin Renqiang Min, Dinghan Shen
  02/02/2018

• Grounded Objects and Interactions for Video Captioning

  ViGIL NIPS 2017 Workshop
  1-9, 2017

  Chih-Yao Ma, Asim Kadav, Iain Melvin, Zsolt Kira, Ghassan AlRegib, Hans Peter Graf
  12/08/2017

• On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models

  NIPS 2017
  1-10, 2017

  Adarsh Prasad, Alexandru Niculescu-Mizil, Pradeep Ravikumar
  12/04/2017

• Exemplar-Centered Supervised Shallow Parametric Data Embedding

  IJCAI 2017
  pp. 2749-2485, 2017

  Martin Renqiang Min, Hongyu Guo, Dongjin Song
  08/19/2017

• A Context-aware Attention Network for Interactive Question Answering

  KDD 2017
  pp. 927-935, 2017

  Huayu Li, Martin Renqiang Min, Yong Ge, Asim Kadav
  08/13/2017

• Detecting Positive Medical History Mentions

  SIGIR 2017
  pp. 1-4, 2017

  Bing Bai, Pierre-Francois Laquerre, Richard Jackson, Robert Stewart
  08/07/2017

• Adaptive Feature Abstraction for Translating Video to Language

  ICLR 2017
  pp. 1-4, 2017

  Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin
  04/24/2017

• Pruning Filters for Efficient ConvNets

  ICLR 2017
  pp. 1-13, 2017

  Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, Hans Peter Graf
  04/24/2017

• Label Filters for Large Scale Multilabel Classification

  AISTATS 2017
  JMLR: W&CP, Vol:54, 2017

  Alexandru Niculescu-Mizil, Ehsan Abbasnejad
  04/20/2017

• Analogy-based Reasoning With Memory Networks for Future Prediction

  NIPS 2016 COCO Workshop
  pp. 1-9, 2016

  Daniel Andrade, Bing Bai, Ramkumar Rajendran, Yotaro Watanabe
  12/09/2016

• Knowledge Based Factorized High Order Sparse Learning Models

  MLCB 2015
  pp.. 1-5, 2015

  Sanjay Purushotham, Martin Renqiang Min, Jay C.-C. Kuo, Mark Gerstein
  12/12/2015

• MALT: Distributed Data-Parallelism for Existing ML Applications

  NIPS LearningSys Workshop (NIPS LearningSys '15)
  pp. 1-6, 2015

  Hao Li, Asim Kadav, Erik Kruus
  12/12/2015

• Random Walk Distributed Dual Averaging Method For Decentralized Consensus Optimization

  NIPS Optimization Workshop (NIPS OPT'15)
  pp. 1-5, 2015

  Cun Mu, Asim Kadav, Erik Kruus, Martin Renqiang Min
  12/11/2015

• High-Order Neural Networks and Kernel Methods for Peptide-MHC Binding Prediction

  Bioinformatics
  pp. 1-7, 2015

  Pavel P. Kuksa, Martin Renqiang Min, Rishabh Dugar, Mark Gerstein
  07/23/2015

• High-Order Neural Networks and Kernel Methods for Peptide-MHC Binding Prediction

  NIPS 2014 Workshop on Machine Learning in Computational Biology
  pp. 1-4, 2014

  Pavel P. Kuksa, Martin Renqiang Min, Rishabh Dugar, Mark Gerstein
  12/13/2014

• Ensemble Learning Based Sparse High-Order Boltzmann Machine for Unsupervised Feature Interaction Identification

  NIPS Workshop on Machine Learning in Computational Biology
  pp. 1-4, 2014

  Martin Renqiang Min, Xia Ning, Yanjun Qi, Chao Cheng, Anthony Bonner, Mark Gerstein
  12/13/2014

• A Deep Learning Model for Structured Outputs with High-order Interaction

  NIPS workshop on Representation and Learning Methods for Complex Outputs
  pp. 1-6, 2014

  Hongyu Guo, Xiaodan Zhu, Martin Renqiang Min
  12/12/2014

• Factorized Sparse Learning Models with Interpretable High Order Feature Interactions

  20th ACM SIGKDD Confeence on nowledge Discovery and Data Mining,
  NYC, New York

  Sanjay Purushotham, Martin Renqiang Min, C.-C. Jay Kuo, Rachal Ostroff
  08/24/2014

• Deep Semantic Embedding

  Workshop on Semantic Matching in Information Retrieval (SMIR 2014), co-located with the 37th International ACM SIGIR Conference
  1204:pp. 46-52, Eds. J. Gonzalo, H. Li, A. Moschitti, J. Xu, Queensland, Australia

  Hao Wu, Martin Renqiang Min, Bing Bai
  07/11/2014

• Interpretable Sparse High-Order Boltzmann Machines

  17th International Conference on Artificial Intelligence and Statistics (AISTATS 2014)
  JMLR: W&CP 33:pp. 614-622, Reykjavik, Iceland

  Martin Renqiang Min, Xia Ning, Chao Cheng, Mark Gerstein
  04/22/2014

• An Integrated Approach to Blood-Based Cancer Diagnosis and Biomarker Discovery

  Pacific Symposium on Biocomputing (PSB 2014)
  19:87-98, 2014

  Martin Renqiang Min, Salim Chowdhury, Yanjun Qi, Alex Stewart, Rachel Ostroff
  01/06/2014

• Interpretable Sparse High-Order Boltzmann Machines for Transcription Factor Interaction Identification

  2013 NIPS Workshop on Machine Learning in Computational Biology, Lake Tahoe, NV
  http://mlcb.org/

  Martin Renqiang Min, Xia Ning, Chao Cheng, Mark Gerstein
  12/10/2013

• Developing Predictive Models Using Electronic Medical Records: Challenges and Pitfalls

  AMIA 2013 Annual Symposium
  pp. 1109-1115, 2013

  Chris Paxton, Alexandru Niculescu-Mizil, Suchi Saria
  11/16/2013

• Biological Sequence Classification with Multivariate String Kernels

  IEEE/ACM Transactions on Computational Biology and Bioinformatics
  10(5):pp.1201-1210, 2013

  Pavel P. Kuksa
  10/01/2013

• Classification of Mitotic Figures with Convolutional Neural Networks and Seeded Blob Features

  Journal of Pathology Informatics
  4(9): DOI: 10.4103/2153-3539.112694, 2013

  Christopher Malon, Eric Cosatto
  10/01/2013

• Answer Extraction by Recursive Parse Tree Descent

  Proceedings of the Workshop on Continuous Vecotr Space Models and their Compositionality, Sofia, Bulgaria
  pp: 110-118, August 9, 2013. 2013 Association for Computational Linguistics

  Christopher Malon, Bing Bai
  08/04/2013

• Controlling the Precision-Recall Tradeoff in Differential Dependency Network Analysis

  Seventh International Workshop on Machine Learning in Systems Biology
  pp. 1-5, 2013

  Diane Oyen, Alexandru Niculescu-Mizil, Rachel Ostroff, Alex Stewart
  07/19/2013

• NECLA at the Medical Natural Language Processing Pilot Task (MedNLP)

  Proceedings of the 10th NTCIR Conference, Tokyo, Japan
  http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings10/NTCIR/toc_ntcir.html#MEDNLP

  Pierre-Francois Laquerre, Christopher Malon
  06/18/2013

• Automatic classification of hepatocellular carcinoma images based on nuclear and structural features

  Medical Imaging 2013: Digital Pathology (Eds. M.N. Gurcan, A. Madabhushi)
  Proc. of SPIE Vol. 8676 86760Y-1-6, 2013 SPIE

  Tomoharu Kiyuna, Akira Saito, Atsushi Marugame, Yoshiko Yamashita, Maki Ogura, Eric Cosatto, Tokiya Abe, Akinori Hashiguchi, Michiiee Sakamoto
  02/09/2013

• Automated gastric cancer diagnosis on H&E-stained sections; training a classifier on a large scale with multiple instance machine learning

  Proceedings of SPIE: Medical Imaging 2013, Digital Pathology (Eds. M.N. Gurcan, A. Madabushi)
  Vol. 8676:pp. 867605-1-9, 2013 SPIE

  Eric Cosatto, Pierre-Francois Laquerre, Christopher Malon, Hans Peter Graf, Akira Saito, Tomoharu Kiyuna, Atsushi Marugame, Kenichi Kamijo
  02/09/2013

• Dawn of the digital diagnosis assisting system, can it open a new age for pathology?

  Proceedings of SPIE: Medical Imaging 2013, Digital Pathology (Eds. M.N. Gurcan, A. Madabushi)
  Vol. 8676 867602-1-16, 2013 SPIE

  Akira Saito, Eric Cosatto, Tomoharu Kiyuna, Michiiee Sakamoto
  02/09/2013

• Learning the Dependency Structure of Latent Factors

  NIPS 2012, Lake Tahoe, NV
  http://nips.cc/Conferences/2012/Program/event.php?ID=3247

  Yunlong He, Yanjun Qi, Koray Kavukcuoglu, Haesun Park
  12/03/2012

• Bayesian Logistic Regression for Hierarchical Classification

  Neural Information Processing Systems Conference and Workshop (NIPS 2012)
  Lake Tahoe, NV

  Alexandru Niculescu-Mizil
  12/03/2012

• Large-scale Image Classification Using Supervised Spatial Encoder

  The 21st Conference of the International Association for Pattern Recognition (ICPR2012), Tsukuba Science City, Japan
  pp. 581-584, 978-4-9906441-0-9 ©2012 ICPR

  Dmitriy Bespalov, Yanjun Qi, Bing Bai, Ali Shokoufandeh
  11/12/2012

• Slot-Filling by Substring Extraction at TAC KBP 2012 (Team Papelo)

  NIST Text Analysis Conference
  Gaithersburg, Maryland

  Christopher Malon, Bing Bai, Kazi Saidul Hasan
  11/05/2012

• Sentiment Classification with Supervised Sequence Embedding

  ECML 2012, Bristol, UK
  http://www.ecmlpkdd2012.net/programme/schedule

  Dmitriy Bespalov, Yanjun Qi, Bing Bai, Ali Shokoufandeh
  09/24/2012

• Efficient Evaluation of Large Sequence Kernels

  The 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Beijing, China
  KDD’12, August 12–16, 2012, Beijing, China, 2012 ACM 978-1-4503-1462-6 /12/08

  Pavel P. Kuksa, Vladimir Pavlovic
  08/12/2012

• 2D similarity kernels for biological sequence classification

  11th International Workshop on Data Mining in Bioinformatics (BIOKDD '12), Beijing, China
  BIOKDD'12 August 12, 2012, Beijing, China, 2012 ACM 978-1-4503-1552-4

  Pavel P. Kuksa
  08/12/2012

• A Binary Classification Framework for Two-Stage Multiple Kernel Learning

  Proceedings of the 29th International Conference on Machine Learning 2012, Edinburgh, Scotland
  June 26 - July 1, 2012 Omnipress; ISBN 978-1-4503-1285-1

  Abhishek Kumar, Alexandru Niculescu-Mizil, Koray Kavukcoglu, Hal Daume
  06/26/2012

• A Unified Multitask Architecture for Predicting Local Protein Properties

  PLoS ONE
  7(3):e32235. DOI:10.1371/journal.pone.0032235

  Yanjun Qi, Merja Oja, Jason Weston, William Stafford Noble
  03/26/2012

• Mitotic Figure Recognition: Agreement Among Pathologists and Computerized Detector

  Analytical Cellular Pathology
  35:pp. 97-100, 2012

  Christopher Malon, Elena Brachtel, Eric Cosatto, Hans Peter Graf, Atsushi Kurata, Masahiko Kuroda, John S. Meyer, Akira Saito, Shulin Wu, Yukako Yagi
  03/07/2012

• Structured Latent Factor Analysis

  NIPS Workshop: Challenges in Learning Hierarchical Models: Transfer Learning and Optimization, Sierra Nevada, Spain
  http://sites.google.com/site/nips2011workshop/schedule

  Yunlong He, Yanjun Qi, Koray Kavukcuoglu, Haesun Park
  12/17/2011

• Sentiment Classification Based on Supervised Latent Ngram Analysis

  CIKM'11
  pp. 375-382, 2011

  Dmitriy Bespalov, Bing Bai, Yanjun Qi, Ali Shokoufandeh
  10/24/2011

• Dynamic Radial Contour Extraction by Splitting Homogeneous Areas

  CAIP 2011, Part I, LNCS 6854
  A. Berciano et al. (Eds), pp. 269-277, Springer-Verlag, Berlin Heidelberg 2011

  Christopher Malon, Eric Cosatto
  08/29/2011

• Inductive Transfer for Bayesian Network Structure Learning

  JMLR: Workshop and Conference Proceedings: Workshop on Unsupervised and Transfer Learning
  7:1-10, 2011

  Alexandru Niculescu-Mizil, Rich Caruana
  07/02/2011

• On Inferring Image Label Information Using Rank Minimization for Supervised Concept Embedding

  SCIA 2011
  A. Heyden and F. Kahl (Eds.): LNCS 6688, pp. 102-113, Springer-Verlag Berlin Heidelberg 2011

  Dmitriy Bespalov, Anders Lindbjerg Dahl, Bing Bai, Ali Shokoufandeh
  05/23/2011

• Semi-Supervised Convolution Graph Kernels for Relation Extraction

  2011 SIAM International Conference on Data Mining
  pp. 510-521, 2011

  Xia Ning, Yanjun Qi
  04/28/2011

• Sparse Latent Semantic Analysis

  2011 SIAM International Conference on Data Mining
  pp. 474-485, 2011

  Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G. Carbonell
  04/28/2011

• Detecting Remote Evolutionary Relationships among Proteins by Large-Scale Semantic Embedding

  PLoS Computational Biology
  7(1):1-8, 2011

  Iain Melvin, Jason Weston, William Stafford Noble, Christina Leslie
  01/03/2011