000 | 04243nam a22005655i 4500 | ||
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008 | 121227s1997 gw | s |||| 0|eng d | ||
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_a9783540684312 _9978-3-540-68431-2 |
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_a10.1007/3-540-62685-9 _2doi |
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050 | 4 | _aQ334-342 | |
050 | 4 | _aTA347.A78 | |
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_aComputational Learning Theory _h[electronic resource] : _bThird European Conference, EuroCOLT '97, Jerusalem, Israel, March 17 - 19, 1997, Proceedings / _cedited by Shai Ben-David. |
250 | _a1st ed. 1997. | ||
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c1997. |
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300 |
_aCCCXLVIII, 338 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v1208 |
|
505 | 0 | _aSample compression, learnability, and the Vapnik-Chervonenkis dimension -- Learning boxes in high dimension -- Learning monotone term decision lists -- Learning matrix functions over rings -- Learning from incomplete boundary queries using split graphs and hypergraphs -- Generalization of the PAC-model for learning with partial information -- Monotonic and dual-monotonic probabilistic language learning of indexed families with high probability -- Closedness properties in team learning of recursive functions -- Structural measures for games and process control in the branch learning model -- Learning under persistent drift -- Randomized hypotheses and minimum disagreement hypotheses for learning with noise -- Learning when to trust which experts -- On learning branching programs and small depth circuits -- Learning nearly monotone k-term DNF -- Optimal attribute-efficient learning of disjunction, parity, and threshold functions -- learning pattern languages using queries -- On fast and simple algorithms for finding Maximal subarrays and applications in learning theory -- A minimax lower bound for empirical quantizer design -- Vapnik-Chervonenkis dimension of recurrent neural networks -- Linear Algebraic proofs of VC-Dimension based inequalities -- A result relating convex n-widths to covering numbers with some applications to neural networks -- Confidence estimates of classification accuracy on new examples -- Learning formulae from elementary facts -- Control structures in hypothesis spaces: The influence on learning -- Ordinal mind change complexity of language identification -- Robust learning with infinite additional information. | |
520 | _aThis book constitutes the refereed proceedings of the Third European Conference on Computational Learning Theory, EuroCOLT'97, held in Jerusalem, Israel, in March 1997. The book presents 25 revised full papers carefully selected from a total of 36 high-quality submissions. The volume spans the whole spectrum of computational learning theory, with a certain emphasis on mathematical models of machine learning. Among the topics addressed are machine learning, neural nets, statistics, inductive inference, computational complexity, information theory, and theoretical physics. | ||
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aMachine theory. | |
650 | 0 | _aComputer science. | |
650 | 1 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aFormal Languages and Automata Theory. |
650 | 2 | 4 | _aTheory of Computation. |
700 | 1 |
_aBen-David, Shai. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783540626855 |
776 | 0 | 8 |
_iPrinted edition: _z9783662213094 |
830 | 0 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v1208 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/3-540-62685-9 |
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