Rómer E. Rosales, Ph.D.

romer[at]csail.mit.edu

Principal Scientist at:LinkedIn




 

Research/Applied Areas of Interest


 

Development of novel machine learning concepts/algorithms

Graphical Models, approximate inference, and structure learning

Convex optimizaton and machine learning

Scalable and distributed machine learning

Crowdsourcing with machine learning

Information retrieval and text analysis

Applications to data mining: computational advertising, predictive models in medicine, text-mining

Representation and probabilistic models in computer vision and image processing
3D articulated body pose estimation from single monocular images

Graphics and visualization of complex data 

 

News  


NIPS 2013 Workshop on Personalization (papers now available) New!


Publications  


Yan Yan, Rómer Rosales, Glenn Fung, Ramanathan Subramanian, and Jennifer Dy

Learning from Multiple Annotators with Varying Expertise (pdf)

Machine Learning Journal, June 2014, Volume 95, Issue 3, pp 291-327.


Liang Tang, Rómer Rosales, Ajit Singh, and Deepak Agarwal

Automatic Ad Format Selection via Contextual Bandits (pdf)

In Proc. Conference on Information and Knowledge Management (CIKM) 2013.


Olivier Chapelle, Eren Manavoglu, and Rómer Rosales

Simple and Scalable Response Prediction for Display Advertising (pdf)

ACM Transactions on Intelligent Systems and Technology (TIST) 2013.


Yan Yan, Rómer Rosales, Glenn Fung, Faisal Farooq, Bharat Rao, and Jennifer Dy

Active Learning from Multiple Knowledge Sources (pdf)

In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS) 2012.


Rómer Rosales, Haibin Cheng, and Eren Manavoglu

Post-Click Conversion Modeling and Analysis for NGD Display Advertising (pdf)

In Proc. International Conference on Web Search and Data Mining (WSDM) 2012.


Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, and R. Bharat Rao

Bayesian Co-Training  (pdf)

Journal of Machine Learning Research (JMLR), Volume 12. p. 2649--2680, 2011.


Rómer Rosales and Olivier Chapelle

Attribute Selection by Measuring Information on Reference Distributions  (pdf)

Tech Pulse Conference, Yahoo! 2011.


Yan Yan, Rómer Rosales, Glenn Fung, and Jennifer Dy

Active Learning from Crowds  (pdf)

In Proc. International Conference on Machine Learning (ICML) 2011.


Faisal Farooq, Glenn Fung, Rómer Rosales, Balaji Krishnapuram, Shipeng Yu, Jude Shavlik, and Raju Kucherlapati

On-line Proceedings of the NIPS Workshop on Predictive Models in Personalized Medicine

Neural Information Processing Systems Workshops 2010.

Rómer Rosales, Faisal Farooq, Balaji Krishnapuram, Shipeng Yu, and Glenn Fung

Automated Identification of Medical Concepts and Assertions in Medical Text  (pdf)

In Proc. American Medical Informatics Association Conference (AMIA) 2010.

Yan Yan, Rómer Rosales, Glenn Fung, and Jennifer Dy

Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario (pdf)

In Proc. Conference on Uncertainty in Artificial Intelligence (UAI) 2010.


Yan Yan, Glenn Fung, Jennifer Dy, and Rómer Rosales

Medical Coding Classification by Leveraging Inter-Code Relationships (pdf)

In Proc. Conference on Knowledge Discovery and Data Mining (KDD) 2010.


Rómer Rosales and R. Bharat Rao (Editors)

Special Issue on Mining Medical Data  

Journal of Data Mining and Knowledge Discovery (Springer) 2010.


Yan Yan, Rómer Rosales, Glenn Fung, Mark Schmidt, Gerardo Hermosillo, Luca Bogoni, Linda Moy, and Jennifer Dy

Modeling Annotator Expertise: Learning when Everybody Knows a Bit of Something (pdf)

In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS) 2010.


Mark Schmidt, Glenn Fung, and  Rómer Rosales

Optimization Methods for L1 Regularization(pdf)

University of British Columbia Technical Report, 2009.


Volkan Vural, Glenn Fung, Rómer Rosales, and Jennifer Dy.

Multi-Class Classifiers and Their Underlying Shared Structure (pdf

In Proc. International Joint Conference on Artificial Intelligence (IJCAI) 2009.


Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, and R. Bharat Rao. 

Active Sensing (pdf

In Proc. International Conference on Artificial Intelligence and Statistics (AISTATS) 2009.


Marianne Mueller, Rómer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, and Stefan Kramer

Subgroup Discovery for Test Selection: A Novel Approach and its Application to Breast Cancer Diagnosis (pdf

In Proc. Intelligent Data Analysis (IDA) 2009.


Marianne Mueller, Rómer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, and Stefan Kramer

Data-Efficient Information-Theoretic Test Selection (pdf

In Proc. Conference on Artificial Intelligence in Medicine (AIME) 2009.


Wei Tong, Rómer Rosales, and Glenn Fung 

Automatic Discrimination of Mislabeled Training Points for Large Margin Classifiers (pdf

In Proc. (Snowbird) Machine Learning Workshop 2009.


Shipeng Yu, Glenn Fung, Rómer Rosales and R. Bharat Rao. 

Privacy-Preserving Cox Regression for Medical Survival Analysis (pdf

In Proc. Knowledge Discovery and Data Mining (KDD) 2008.


Mark Schmidt, Kevin Murphy, Glenn Fung,  and Rómer Rosales

Discriminative Structure Learning in Random Fields and an Application for Heart Motion Abnormality Detection  (pdf)

In Proc. Computer Vision and Pattern Recognition (CVPR) 2008.

R. Bharat Rao, Glenn Fung, and Rómer Rosales
On the Dangers of Cross-Validation. An Experimental Evaluation 
(pdf)

In Proc. SIAM Data Mining (SDM) 2008.

Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, Harald Steck, and R. Bharat Rao
Bayesian Co-Training 
(pdf)

In Proc. Neural Information Processing Systems (NIPS) 2007.

Rómer Rosales, Praveen Krishnamurthy, and R. Bharat Rao
Semi-supervised Active Learning for Modeling Medical Concepts from Free Text 
(pdf)

In Proc. International Conference on Machine Learning Applications (ICMLA) 2007.

Mark Schmidt, Glenn Fung, and Rómer Rosales
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches 
(pdf, slides)

In Proc. European Conference on Machine Learning (ECML) 2007.

Glenn Fung, Rómer Rosales, and R. Bharat Rao
Feature Selection and Kernel Design via Linear Programming 
(pdf)

In Proc. International Joint Conference on Artificial Intelligence (IJCAI) 2007.

 

Maleeha Qazi, Glenn Fung, Sriram Krishnan, Rómer Rosales, Harald Steck, R. Bharat Rao, Don Poldermans, and Dhanalakshmi Chandrasekaran 
Automated HeartWall Motion Abnormality Detection From Ultrasound Images using Bayesian Networks 
(pdf)

Distinguished Paper Award

In Proc. International Joint Conference on Artificial Intelligence (IJCAI) 2007.

 

Rómer Rosales and Glenn Fung
Learning 'Sparse' Metrics via Linear Programming 
(pdf)

In Proc. Knowledge Discovery and Data Mining (KDD) 2006.

 

Rómer Rosales and Stan Sclaroff
Combining generative and discriminative models in a framework for articulated pose estimation 
(pdf)

International Journal of Computer Vision (IJCV) Volume 67 (3) p. 251-276, 2006

Example applications

 

Glenn Fung, Rómer Rosales, and Balaji Krishnapuram
Learning Rankings via Convex Hull Separation
(pdf)

In Proc. Neural Information Processing Systems (NIPS) 2005.

 

Rómer Rosales and Tommi Jaakkola
Focused Inference
(pdf|ps|slides)

In Artificial Intelligence and Statistics (AISTATS). Jan 2005.

 

Rómer Rosales, Kannan Achan, and Brendan Frey
Learning to Cluster using Local Neighborhood Structure
(pdf|ps|slides)

In Proc. International Conference on Machine Learning (ICML).  Jul 2004.

 

Rómer Rosales, Kannan Achan, and Brendan Frey
Unsupervised Image Translation
(pdf|ps)

In Proc. International Conference on Computer Vision (ICCV).  Oct 2003.

Example translations

 

Rómer Rosales and Brendan Frey
Learning Generative Models of Affinity Matrices
(pdf|ps)

In Proc. 19th Conference on Uncertainty in Artificial Intelligence (UAI). Aug 2003.

 

Rómer Rosales, Kannan Achan, and Brendan Frey
Translating Images by Unsupervised Estimation of Switching Filters
(pdf|ps)

In Proc. IEEE Workshop on Statistical Signal Processing  (SSP) (invited paper).  Sep 2003.

   

Rómer Rosales and Stan Sclaroff

A Framework for Heading-Guided Recognition of Human Activity (pdf| ps)

Computer Vision and Image Understanding Journal (CVIU)  2003. 


Rómer Rosales and Stan Sclaroff
Algorithms for Interence in the SMA

In Proc. 5th IEEE International Conference on Automatic Face and Gesture Recognition (FG2002). Presented in FG2002, Washington, DC, May 2002.  .


Rómer Rosales
The Specialized Mappings Architecture with Applications to Vision-Based Estimation of Articulated Body Pose (pdf|ps|Abstract)

Ph.D. Thesis. Jan 2002. 

 

Rómer Rosales and Stan Sclaroff

Learning Body Pose Via Specialized Maps (pdf)

In Proc. Neural Information Processing Systems NIPS-14, 2002. Presented at NIPS, Vancouver, BC, Dec 2001.

 

Stan Sclaroff, George Kollios, Margrit Betke, and Rómer Rosales

Motion Mining

Lecture Notes in Computer Science; Vol 2184. Proc. 2nd International Workshop on Multimedia Databases and Image Communication, 2001

 

Rómer Rosales, Matheen Siddiqui, Joni Alon, and Stan Sclaroff

3D Body Pose Using Uncalibrated Cameras (ps.gz)

In Proc. IEEE Computer Vision and Pattern Recognition (CVPR). Presented at CVPR, Kauai, Hawaii, Dec 2001.

 

Rómer Rosales, Vassilis Athitsos, and Stan Sclaroff

3D Hand Pose Reconstruction Using Specialized Mappings (pdf)

In Proc. IEEE International Conference on Computer Vision (ICCV). Presented at ICCV, Vancouver, BC, Canada, Jul 2001.

 

Rómer Rosales and Stan Sclaroff

Specialized Mappings and the Estimation of Human Body Pose from a Single Image (ps)

In Proc. IEEE Workshop on Human Motion (HUMO). Presented at HUMO, Austin, TX, Dec 2000.

 

Rómer Rosales and Stan Sclaroff

Inferring Body Pose Without Tracking Body Parts (ps.Z)

In Proc. IEEE Computer Vision and Pattern Recogniton (CVPR). Presented at CVPR, Hilton Head Island, SC, Jun 2000.

 

Rómer Rosales and Stan Sclaroff

Learning and Synthesizing Human Body Pose and Motion

In Proc. 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG2000). Presented at FG200, Grenoble, France, 2000.

 

Rómer Rosales and Stan Sclaroff

Trajectory Guided Recognition

In Proc. SPIE 99. Presented at SPIE, Boston, MA, 1999.

   

Rómer Rosales and Stan Sclaroff

3D Trajectory Recovery for Tracking Multiple Objects and Trajectory Guided Recognition of Actios (ps.Z)

In Proc. IEEE Computer Vision and Pattern Recognition (CVPR). Presented at CVPR, Fort Collins, CO, 1999

 

Rómer Rosales

Recognition of Human Action Using Moment-Based Features (ps.Z)

Boston University Computer Science Technical Report BU 1998-020, Boston, MA, 1998.

 

Rómer Rosales and Stan Sclaroff

Improved Tracking of Multiple Humans with Trajectory Prediction and Occlusion Modeling (ps.Z)

In Proceedings IEEE CVPR Workshop on the Interpretation of Visual Motion. Presented at CVPR,  Santa Barbara, CA, 1998

 

Patents 


 

Guiding Differential Diagnosis through Information Maximization.
US Patent 7877272


Medical Ontologies for Computer Assisted Clinical Decision Support.
US Patent 7840512


Learning or Inferring Medical Concepts from Medical Transcripts.
US Patent 7840511


Other Patents


 

Other 


 

Oksana Yakhnenko, Lucian Lita, Rómer Rosales, and Stefan Niculescu

Principled Generative-Discriminative Hybrid Hidden Markov Model. 

In Neural Information processing Systems, Workshop on Representations and Inference on Probability Distributions (NIPS) 2007. 

 

T. Wilmes, K. Bohy, A. Gilson, R. Rosales, S. Krishnan, S. Niculescu, M. Qazi, F. Rahmanian, W. Landi, B. Rao. 

Automated Chart Abstraction Can Provide Highly Accurate Data Extraction For Clinical Quality Measures: Assessment of REMIND for CMS Heart Failure Measures. 

American Heart Association, Circulation 114: II_864-a, 2006. 

 

Venk Gottipaty, Rómer Rosales, Prasad Aloni, John Beard, Paul Zimmermann, Linda Adams, R. Bharat Rao. 

Automated Identification of MADIT-II Eligible Patients Using REMIND Artificial Intelligence Software. 

American Heart Association, Circulation 111:e310-e359,  2005.

 

Rómer Rosales and Brendan Frey

Generative Models of Affinity Matrices (html|ps 4 s/p)

Presented at NIPS Workshop on Spectral Methods in Dimensionality Reduction, Clustering, and Classification. Vancouver, BC, Dec 2002.

   


Modified July 2013