[PDF] Top 20 Refined Error Bounds for Several Learning Algorithms
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Refined Error Bounds for Several Learning Algorithms
... active learning algorithms referred to as disagreement-based (or sometimes as mellow ), including several methods possessing desirable properties such as robustness to classification noise ...active ... See full document
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Conspiracies between learning algorithms, circuit lower bounds, and pseudorandomness
... for learning, and if so, what kinds of lower bounds would follow using such an ...non-trivial learning algorithms yield lower bounds for bounded-error probabilistic exponential ... See full document
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Error bounds for general mixed quasivariational inequalities
... iterative algorithms for solving variational inequalities, and related op- timization ...developing several iterative methods for solving variational ... See full document
16
Best Arm Identification for Contaminated Bandits
... active learning in the context of robust ...complexity bounds for high-probability estimation of the first two robust moments (median and median absolute deviation) from contaminated ...adapt several ... See full document
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O pt i ma l i t yo f Uni v e r s a l Ba y e s i a n Se q ue nce P r e di ct i o n f o r Ge ne r a l L o s sa nd Al pha be t
... online learning of classification tasks are special ...the algorithms, the settings, and the proofs are quite different, the PEA bounds and our error bound have the same ...environment, ... See full document
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Generalization Error Bounds for Threshold Decision Lists
... of learning threshold decision lists. As mentioned, heuristics for learning threshold decision lists were studied by Marchand and Golea (1993), and although no theoretical generalization error ... See full document
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Algorithmic Stability and Meta-Learning
... transfer learning is analysed, where samples drawn from different learning tasks of an environment are used to improve the learners performance on a new ...generalisation error bounds for such ... See full document
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Pycobra: A Python Toolbox for Ensemble Learning and Visualisation
... Machine Learning competitions – the celebrated Netflix Challenge (as are re- peatedly Kaggle competitions) was won by an ensemble technique (see for example Bell and Koren, 2007, for a ...of several ensem- ... See full document
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Beyond Fano's Inequality: Bounds on the Optimal F-Score, BER, and Cost-Sensitive Risk and Their Implications
... transmission error probability of a noisy communication channel to standard information theoretic quantities such as conditional entropy and mutual information (Shannon, ...machine learning perspective, we ... See full document
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Generalization Error Bounds for Bayesian Mixture Algorithms
... perhaps several constraint ...similar bounds in the con- text of Gaussian processes, and their relevance to real-world ...our bounds, but a systematic numerical investigation still needs to be ... See full document
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Quantum algorithms and lower bounds for convex optimization
... Convex optimization has been a central topic in the study of mathematical optimization, the- oretical computer science, and operations research over the last several decades. On the one hand, it has been used to ... See full document
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A survey on error bounds for lower semicontinuous functions
... In the previous subsection, we gave a characterization of the existence of a global error bound in terms of the strong slope. So it is necessary to estimate the strong slope in order to apply this result. In fact ... See full document
17
Accurate Error Bounds for the Eigenvalues of the Kernel Matrix
... the error severely for all but the first four ...our bounds (solid lines) scale with the eigenvalues resulting in a bound which matches the true approximation error significantly ...scaling ... See full document
26
Application of Fixed Point Theorem and Error Bounds
... Proof: Suppose that d x g x ( , ( ) ) = − x g x ( ) for x ∈ k . By the mean-value theorem and the given condi- tion , g x ( ) is a contraction mapping of the complete metric space k into itself . Hence , by Corollary 1.4 ... See full document
6
Best Error Bounds of Quartic Spline Interpolation
... best error bound for quartic spline ...uniqueness, error bounds and convergence properties of deficient quartic spline interpolation which matches the given function of mesh points and mid points, ... See full document
5
Reinforcement Learning in Finite MDPs: PAC Analysis
... The terminology, PAC, in this definition is borrowed from Angluin (1988) for the distribution- free supervised-learning model of Valiant (1984). One thing to note is that we only require a PAC- MDP algorithm to ... See full document
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A Refined Margin Analysis for Boosting Algorithms via Equilibrium Margin
... generalization error of a voting classifier that does not depend on how many classifiers were combined, but only on the margin distribution over the training set, the number of the training examples and the size ... See full document
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Trellis coded modulation on time dispersive channels
... Chapter 7 Analytical Performance Bounds Preliminaries 7.2 Union Bound on Error-Event Probability 7.3 Upper Bounds on Conditional Pairwise Error Probability 7.3.1 Viterbi Bound 7.3.2 Cher[r] ... See full document
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Application of Refined LSA and MD5 Algorithms in Spam Filtering
... When generating “E-mail fingerprint”, configuration of size of the sliding window will also affect performance and efficiency of the LSA and MD5 algorithms in spam filtering. As shown in Figure 2, the larger the ... See full document
6
Eigenvalues of complementary Lidstone boundary value problems
... There is a vast literature on Lidstone interpolation and boundary value problems. The Lidstone interpolation has a long history from 1929 when Lidstone [8] introduced a generalization of Taylor ’ s series that ... See full document
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