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Displaying 1-13 out of 13 total
Automatic Detection of HIV Drug Resistance-Associated Mutations
Found in: Machine Learning and Applications, Fourth International Conference on
By Betty Y. Cheng, Jaime G. Carbonell
Issue Date:December 2010
pp. 528-533
Each HIV-1 patient has a diverse population of virus strains in his/her body as the virus quickly replicates and mutates, requiring a combination drug therapy optimized to the patient’s unique viral population. Towards this goal, prediction systems have be...
 
Accelerated Gradient Method for Multi-task Sparse Learning Problem
Found in: Data Mining, IEEE International Conference on
By Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbonell
Issue Date:December 2009
pp. 746-751
Many real world learning problems can be recast as multi-task learning problems which utilize correlations among different tasks to obtain better generalization performance than learning each task individually. The feature selection problem in multi-task s...
 
Learning Approaches for Detecting and Tracking News Events
Found in: IEEE Intelligent Systems
By Yiming Yang, Jaime G. Carbonell, Ralf D. Brown, Thomas Pierce, Brian T. Archibald, Xin Liu
Issue Date:July 1999
pp. 32-43
<p>This article studies the effective use of information-retrieval and machine-learning techniques in a new task, event detection and tracking. The objective is to automatically detect novel events from chronologically ordered streams of news stories...
 
Steps Toward Knowledge-Based Machine Translation
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Jaime G. Carbonell,Richard E. Cullingford,Anatole V. Gershman
Issue Date:April 1981
pp. 376-392
This paper considers the possibilities for knowledge-based automatic text translation in the light of recent advances in artificial intelligence. It is argued that competent translation requires some reasonable depth of understanding of the source text, an...
 
Retrieval and feedback models for blog feed search
Found in: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '08)
By Jaime Arguello, Jaime G. Carbonell, Jamie Callan, Jonathan L. Elsas
Issue Date:July 2008
pp. 2-2
Blog feed search poses different and interesting challenges from traditional ad hoc document retrieval. The units of retrieval, the blogs, are collections of documents, the blog posts. In this work we adapt a state-of-the-art federated search model to the ...
     
A tutorial on natural-language processing
Found in: Proceedings of the ACM '81 conference (ACM 81)
By Gary G. Hendrix, Jaime G. Carbonell
Issue Date:January 1981
pp. 4-8
This tutorial focuses on the problems of enabling computers to communicate with humans in natural languages, such as English and French, as distinguished from formal languages, such as BASIC and FORTRAN. Understanding the computational mechanisms that unde...
     
It pays to be picky: an evaluation of thread retrieval in online forums
Found in: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval (SIGIR '09)
By Jaime G. Carbonell, Jonathan L. Elsas
Issue Date:July 2009
pp. 435-435
Online forums host a rich information exchange, often with contributions from many subject matter experts. In this work we evaluate algorithms for thread retrieval in a large and active online forum community. We compare methods that utilize thread structu...
     
Efficiently learning the accuracy of labeling sources for selective sampling
Found in: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '09)
By Jaime G. Carbonell, Jeff Schneider, Pinar Donmez
Issue Date:June 2009
pp. 1-24
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources ('oracles' or 'experts') with different but unknown reliabilities? With the recent advent ...
     
Suppressing outliers in pairwise preference ranking
Found in: Proceeding of the 17th ACM conference on Information and knowledge mining (CIKM '08)
By Jaime G. Carbonell, Jonathan L. Elsas, Vitor R. Carvalho, William W. Cohen
Issue Date:October 2008
pp. 1001-1001
Many of the recently proposed algorithms for learning feature-based ranking functions are based on the pairwise preference framework, in which instead of taking documents in isolation, document pairs are used as instances in the learning process. One disad...
     
Proactive learning: cost-sensitive active learning with multiple imperfect oracles
Found in: Proceeding of the 17th ACM conference on Information and knowledge mining (CIKM '08)
By Jaime G. Carbonell, Pinar Donmez
Issue Date:October 2008
pp. 1001-1001
Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. Active learning seeks to select the most informative unlabeled instances and ask an omniscient oracle for their la...
     
Optimizing estimated loss reduction for active sampling in rank learning
Found in: Proceedings of the 25th international conference on Machine learning (ICML '08)
By Jaime G. Carbonell, Pinar Donmez
Issue Date:July 2008
pp. 248-255
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of instances in the input space. However, collecting labeled data is growing into a b...
     
Fast learning of document ranking functions with the committee perceptron
Found in: Proceedings of the international conference on Web search and web data mining (WSDM '08)
By Jaime G. Carbonell, Jonathan L. Elsas, Vitor R. Carvalho
Issue Date:February 2008
pp. 2-2
This paper presents a new variant of the perceptron algorithm using selective committee averaging (or voting). We apply this agorithm to the problem of learning ranking functions for document retrieval, known as the "Learning to Rank" problem. Most previou...
     
Default reasoning and inheritance mechanisms on type hierarchies
Found in: Proceedings of the 1980 workshop on Data abstraction, databases and conceptual modeling
By Jaime G. Carbonell
Issue Date:June 1980
pp. 143-154
Type hierarchies abound in Artificial Intelligence, Data Bases and Programming Languages. Although their size, use and complexity differs, all share a central inference mechanism: Inheritance of information, their raison d'etre. This paper discusses variou...
     
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