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» Self Bounding Learning Algorithms
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STOC
1993
ACM
141views Algorithms» more  STOC 1993»
14 years 1 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
ML
2007
ACM
131views Machine Learning» more  ML 2007»
13 years 9 months ago
A primal-dual perspective of online learning algorithms
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Shai Shalev-Shwartz, Yoram Singer
SASO
2009
IEEE
14 years 4 months ago
Distributed W-Learning: Multi-Policy Optimization in Self-Organizing Systems
—Large-scale agent-based systems are required to self-optimize towards multiple, potentially conflicting, policies of varying spatial and temporal scope. As a result, not all ag...
Ivana Dusparic, Vinny Cahill
ICDE
2009
IEEE
179views Database» more  ICDE 2009»
14 years 4 months ago
Self-Tuning, Bandwidth-Aware Monitoring for Dynamic Data Streams
— We present SMART, a self-tuning, bandwidth-aware monitoring system that maximizes result precision of continuous aggregate queries over dynamic data streams. While prior approa...
Navendu Jain, Praveen Yalagandula, Michael Dahlin,...
COLT
2007
Springer
14 years 3 months ago
A Lower Bound for Agnostically Learning Disjunctions
We prove that the concept class of disjunctions cannot be pointwise approximated by linear combinations of any small set of arbitrary real-valued functions. That is, suppose there ...
Adam R. Klivans, Alexander A. Sherstov