Publications

Books    
Technical Reports
 

  • 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

Learning Preferences with Millions of Parameters by Enforcing Sparsity
2010 IEEE International Conference on Data Mining (ICDM2010)
pp. 779-784
Xi Chen, Bing Bai, Yanjun Qi, Qihang Li, Jamie Carbonell
12/13/2010

Label Embedding Trees for Large Multi-Class Tasks
Advances in Neural Information Processing Systems (NIPS 2010)
PDF
Samy Bengio, Jason Weston, David Grangier
12/10/2010

Feature Set Embedding for Incomplete Data
Advances in Neural Information Processing Systems (NIPS 2010)
PDF
David Grangier, Iain Melvin
12/6/2010

Semi-Supervised Abstraction-Augmented String Kernel for Multi-Level Bio-Relation Extraction
ECML PKDD 2010, Part II, LNAI 63222
J.L. Balcazar et al. (Eds): pp. 128-144, Springer-Verlag Berlin Heidelberg 2010
Pavel P. Kuksa, Yanjun Qi, Bing Bai, Ronan Collobert, Jason Weston, Vladimir Pavlovic, Xia Ning
9/20/2010

A Programmable Parallel Accelerator for Learning and Classification
PACT 2010
pp. 273-283
Srihari Cadambi, Abhinandan Majumdar, Michela Becchi, Srimat T. Chakradhar, Hans Peter Graf
9/11/2010

Semi-Supervised Multi-Task Learning for Predicting Interaction Between HIV-1 and Human Proteins
Bioinformatics
Vol. 26 ECCB 2010, pp. i645-652, 2010
Yanjun Qi, Oznur Tastan, Jaime G. Carbonell, Judith Klein-Seetharaman, Jason Weston
8/16/2010

Anderson Localization Makes Adiabatic Quantum Optimization Fail
National Academy of Sciences of the United States of America
Vol. 107: 12446-12450, 2010
Boris Altshuler, Hari Krovi, Jeremie Roland
7/13/2010

Half Transductive Ranking
13th International Conference on Artificial Intelligence and Statistics
JMLR: W&CP 9:49-56, 2010
Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Corinna Cortes, Mehryar Mohri
5/13/2010

Towards Understanding Situated Natural Language
13th International Conference on Artificial Intelligence and Statistics
JMLR: W&CP 9:65-72, 2010
Antoine Bordes, Nicolas Usunier, Ronan Collobert, Jason Weston
5/13/2010

Semi-Supervised Bio-Named Entity Recognition with Word-Codebook Learning
2010 SIAM International Conference on Data Mining
pp. 25-36, 2010  PDF
Pavel P. Kuksa, Yanjun Qi
4/29/2010

Polynomial Semantic Indexing
22nd Advances in Neural Information Processing Systems (NIPS 2009)
PDF
Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri
12/7/2009

Semi-Supervised Sequence Labelling with Self-Learned Feature Class Pattern
IEEE International Conference on Data Mining
pp. 428-437, 2009
Yanjun Qi, Pavel P. Kuksa, Ronan Collobert, Kunihiko Sadamasa, Koray Kavukcuoglu, Jason Weston
12/6/2009

Combining Labeled and Unlabeled Data with Class-Distribution-Feature Learning
The 18th Conference on Information and Knowledge Management (CIKM 2009)
pp. 1737-1740
Yanjun Qi, Ronan Collobert, Pavel P. Kuksa, Koray Kavukcuoglu, Jason Weston
11/2/2009

Supervised Semantic Indexing
The 18th International Conference on Information and Knowledge Management (CIKM 2009)
pp. 187-196, 2009
Bing Bai, Jason Weston, David Grangier, Ronon Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Killian Weinberger
11/2/2009

Mitotic Index of Invasive Breast Carcinoma
Archives of Pathology and Laboratory Medicine
133(11): pp. 1826-1833, 2009
John S. Meyer, Eric Cosatto, Hans Peter Graf
11/1/2009

Learning to Rank with (a lot of) Word Features
Information Retrieval - Special Isue:  Learning to Rank for Information Retrieval
PDF
Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Weinberger
9/23/2009

A New Learning Paradigm:  Learning Using Privileged Information
Neural Networks, Special Issue
Elsevier, Ltd; pp. 544-557
Vladimir Vapnik, Akshay Vashist
9/1/2009

Learning to Rank with Low Rank
SIGIR 2009 LR4IR Workshop
pp. 1-8, 2009
Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Yanjun Qi, Kunihiko Sadamasa, Olivier Chapelle, Kilian Weinberger
7/23/2009

Erratum: SGDQN is Less Careful than Expected
Journal of Machine Learning Research
10: 1737-1754, 2009
Antoine Bordes, Leon Bottou, Patrick Gallinari
7/15/2009

A Massively Parallel Coprocessor for Convolutional Neural Networks
ASAP 2009
pp. 63-60
Murugan Sankaradas, Venkata Jakkula, Srihari Cadambi, Srimat T. Chakradhar, Igor Durdanovic, Eric Cosatto, Hans Peter Graf
7/7/2009

SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent
Journal Of machine Learning Research
10: 1737-1754, 2009
Antoine Bordes, Leon Bottou, Patrick Gallinari
7/1/2009

Deep Learning from Temporal Coherence in Video
2009 International Conference on Machine Learning
PDF
Hossein Mobahi, Ronan Collobert, Jason Weston
6/15/2009

Curriculum Learning
The 26th International Conference on Machine Learning 2009
PDF
Yoshua Bengio, Jerome Louradour, Ronan Collobert, Jason Weston
6/14/2009

Learning Using Hidden Information (Learning with Teacher)
International Joint Conference on Neural Networks
pp. 3188-3195, 2009
Vladimir Vapnik, Akshay Vashist, Natalya Pavlovitch
6/14/2009

Supervised Semantic Indexing
ECIR 2009, Lecture Notes in Computer Science 5478
pp. 761-765, 2009, Springer-Verlag, Berlin
Bing Bai, Jason Weston, Ronan Collobert, David Grangier
4/29/2009

Improvements to the Percolator Algorithm for Peptide Identification from Shotgun Proteomics Data Sets
Journal of Proteome Research, 2009
American Chemical Society
Marina Spivak, Jason Weston, Leon Bottou, Lukas Kall, William Stafford Noble
4/23/2009

A Massively Parallel FPGA-based Coprocessor for Support Vector Machines
FCCM 2009
pp. 115-122, 2009
Srihari Cadambi, Igor Durdanovic, Venkata Jakkula, Murugan Sankaradas, Eric Cosatto, Srimat T. Chakradhar, Hans Peter Graf
4/5/2009