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ICDE
2009
IEEE
140views Database» more  ICDE 2009»
16 years 6 months ago
Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning
One of the most challenging aspects of managing a very large data warehouse is identifying how queries will behave before they start executing. Yet knowing their performance charac...
Archana Ganapathi, Harumi A. Kuno, Umeshwar Dayal,...
EPIA
2003
Springer
15 years 9 months ago
Adaptation to Drifting Concepts
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Gladys Castillo, João Gama, Pedro Medas
COLT
1995
Springer
15 years 8 months ago
On the Learnability and Usage of Acyclic Probabilistic Finite Automata
We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishabi...
Dana Ron, Yoram Singer, Naftali Tishby
COLT
2010
Springer
15 years 2 months ago
Regret Minimization With Concept Drift
In standard online learning, the goal of the learner is to maintain an average loss that is "not too big" compared to the loss of the best-performing function in a fixed...
Koby Crammer, Yishay Mansour, Eyal Even-Dar, Jenni...
FOCS
1994
IEEE
15 years 8 months ago
The Power of Team Exploration: Two Robots Can Learn Unlabeled Directed Graphs
We show that two cooperating robots can learn exactly any strongly-connected directed graph with n indistinguishable nodes in expected time polynomial in n. We introduce a new typ...
Michael A. Bender, Donna K. Slonim