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Alex Ksikes

dblp:69/4922 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%
Artificial intelligence
1 paper
Kernel, tree and ensemble methods · 67% Optimization for machine learning · 33%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › document retrieval › domain-specific retrieval › biomedical information retrieval
biomedical literature search
0.112007
BioText Search Engine: beyond abstract search · Bioinform. 2007
Information retrieval
search engines
0.112007
BioText Search Engine: beyond abstract search · Bioinform. 2007
Machine learning › Kernel, tree and ensemble methods
ensemble learning
0.012004
Ensemble selection from libraries of models · ICML 2004
Machine learning › Kernel, tree and ensemble methods › ensemble learning
ensemble selection
0.012004
Ensemble selection from libraries of models · ICML 2004

Methods — techniques the papers use, named apart from their topics

list view · 0.1grid view · 0.1forward stepwise selection · 0.0
YearPublicationVenuePosition
2007 BioText Search Engine: beyond abstract search
abstract
UNLABELLED: The BioText Search Engine is a freely available Web-based application that provides biologists with new ways to access the scientific literature. One novel feature is the ability to search and browse article figures and their captions. A grid view juxtaposes many different figures associated with the same keywords, providing new insight into the literature. An abstract/title search and list view shows at a glance many of the figures associated with each article. The interface is carefully designed according to usability principles and techniques. The search engine is a work in progress, and more functionality will be added over time. AVAILABILITY: http://biosearch.berkeley.edu.
Marti A. Hearst, Anna Divoli, Harendra Guturu, Alex Ksikes, Preslav Nakov, Michael A. Wooldridge, Jerry Ye
Bioinform.4
2004 Ensemble selection from libraries of models
abstract
We present a method for constructing ensembles from libraries of thousands of models. Model libraries are generated using different learning algorithms and parameter settings. Forward stepwise selection is used to add to the ensemble the models that maximize its performance. Ensemble selection allows ensembles to be optimized to performance metric such as accuracy, cross entropy, mean precision, or ROC Area. Experiments with seven test problems and ten metrics demonstrate the benefit of ensemble selection.
Rich Caruana, Alexandru Niculescu-Mizil, Geoff Crew, Alex Ksikes
ICML4