Richard D. Lawrence

Publication Activity (10 Years)

Years Active: 1994-2015
Publications (10 Years): 0

Top Topics

Multiple Instance Learning

Multiple Instance

Massive Data Streams

Image Annotation

Top Venues

IBM J. Res. Dev.

Publications

Yada Zhu, Jingrui He, Richard D. Lawrence
A general framework for predictive tensor modeling with domain knowledge. Data Min. Knowl. Discov. 29 (6) (2015)
Prem Melville, Vijil Chenthamarakshan, Richard D. Lawrence, James Powell, Moses Mugisha, Sharad Sapra, Rajesh Anandan, Solomon Assefa
Amplifying the voice of youth in Africa via text analytics. KDD (2013)
Shiva Prasad Kasiviswanathan, Gao Cong, Prem Melville, Richard D. Lawrence
Novel document detection for massive data streams using distributed dictionary learning. IBM J. Res. Dev. 57 (3/4) (2013)
Dan Zhang, Jingrui He, Richard D. Lawrence
MI2LS: multi-instance learning from multiple informationsources. KDD (2013)
Dan Zhang, Jingrui He, Luo Si, Richard D. Lawrence
MILEAGE: Multiple Instance LEArning with Global Embedding. ICML (3) (2013)
Arvind Agarwal, Hema Raghavan, Karthik Subbian, Prem Melville, Richard D. Lawrence, David Gondek, James Fan
Learning to rank for robust question answering. CIKM (2012)
Vijil Chenthamarakshan, Prem Melville, Vikas Sindhwani, Richard D. Lawrence
Concept Labeling: Building Text Classifiers with Minimal Supervision. IJCAI (2011)
Dan Zhang, Yan Liu, Luo Si, Jian Zhang, Richard D. Lawrence
Multiple Instance Learning on Structured Data. NIPS (2011)
Vikas Sindhwani, Amol Ghoting, Edison Ting, Richard D. Lawrence
Extracting insights from social media with large-scale matrix approximations. IBM J. Res. Dev. 55 (5) (2011)
Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan
Transfer Latent Semantic Learning: Microblog Mining with Less Supervision. AAAI (2011)
Dan Zhang, Jingrui He, Yan Liu, Luo Si, Richard D. Lawrence
Multi-view transfer learning with a large margin approach. KDD (2011)
Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan
ALPOS: A Machine Learning Approach for Analyzing Microblogging Data. ICDM Workshops (2010)
Prem Melville, Wojciech Gryc, Richard D. Lawrence
Sentiment analysis of blogs by combining lexical knowledge with text classification. KDD (2009)
Jingrui He, Yan Liu, Richard D. Lawrence
Graph-based transfer learning. CIKM (2009)
Vikas Sindhwani, Prem Melville, Richard D. Lawrence
Uncertainty sampling and transductive experimental design for active dual supervision. ICML (2009)
Jingrui He, Yan Liu, Richard D. Lawrence
Graph-Based Rare Category Detection. ICDM (2008)
Prem Melville, Saharon Rosset, Richard D. Lawrence
Customer targeting models using actively-selected web content. KDD (2008)
Claudia Perlich, Prem Melville, Yan Liu, Grzegorz Swirszcz, Richard D. Lawrence, Saharon Rosset
Breast cancer identification: KDD CUP winner's report. SIGKDD Explor. 10 (2) (2008)
Richard D. Lawrence, Claudia Perlich, Saharon Rosset, Jorge Arroyo, Matthew Callahan, J. Matthew Collins, Alexey Ershov, Sheri Feinzig, Ildar Khabibrakhmanov, Shilpa Mahatma, Mark Niemaszyk, Sholom M. Weiss
Analytics-driven solutions for customer targeting and sales-force allocation. IBM Syst. J. 46 (4) (2007)
Claudia Perlich, Saharon Rosset, Richard D. Lawrence, Bianca Zadrozny
High-quantile modeling for customer wallet estimation and other applications. KDD (2007)
Wojciech Gryc, Mary E. Helander, Richard D. Lawrence, Yan Liu, Claudia Perlich, Chandan K. Reddy, Saharon Rosset
Looking for Great Ideas: Analyzing the Innovation Jam. WebKDD/SNA-KDD (2007)
Saharon Rosset, Richard D. Lawrence
Data-Enhanced Predictive Modeling for Sales Targeting. SDM (2006)
Richard D. Lawrence, Se June Hong, Jacques Cherrier
Passenger-based predictive modeling of airline no-show rates. KDD (2003)
Martin Bichler, Jayant Kalagnanam, Kaan Katircioglu, Alan J. King, Richard D. Lawrence, Ho Soo Lee, Grace Y. Lin, Yingdong Lu
Applications of flexible pricing in business-to-business electronic commerce. IBM Syst. J. 41 (2) (2002)
Richard D. Lawrence, George S. Almási, Vladimir Kotlyar, Marisa S. Viveros, Sastry Duri
Personalization of Supermarket Product Recommendations. Data Min. Knowl. Discov. 5 (1/2) (2001)
José E. Moreira, Samuel P. Midkiff, Manish Gupta, Pedro V. Artigas, Marc Snir, Richard D. Lawrence
Java programming for high-performance numerical computing. IBM Syst. J. 39 (1) (2000)
Richard D. Lawrence, George S. Almási, Holly E. Rushmeier
A Scalable Parallel Algorithm for Self-Organizing Maps with Applications to Sparse Data Mining Problems. Data Min. Knowl. Discov. 3 (2) (1999)
Vladimir Kotlyar, Marisa S. Viveros, Sastry Duri, Richard D. Lawrence, George S. Almási
A Case Study in Information Delivery to Mass Retail Markets. DEXA (1999)
Holly E. Rushmeier, Richard D. Lawrence, George S. Almási
Visualizing customer segmentations produce by self organizing maps (case study). IEEE Visualization (1997)
Vasanth Bala, Jehoshua Bruck, Raymond Bryant, Robert Cypher, Peter de Jong, Pablo Elustondo, Daniel D. Frye, Alex Ho, Ching-Tien Ho, Gail Irwin, Shlomo Kipnis, Richard D. Lawrence, Marc Snir
The IBM External User Interface for Scalable Parallel Systems. Parallel Comput. 20 (4) (1994)