Computational learning theory. 14th annual conference, COLT 2001, and 5th European conference, EuroCOLT 2001, Amsterdam, Netherlands, July 16--19, 2001. Proceedings (Q5943777)

The articles of mathematical interest will be reviewed individually. Indexed articles: \textit{Simon, Hans Ulrich}, How many queries are needed to learn one bit of information?, 1-13 [Zbl 0992.68095] \textit{Schmitt, Michael}, Radial basis function neural networks have superlinear VC dimension, 14-30 [Zbl 0992.68107] \textit{Bousquet, Olivier; Warmuth, Manfred K.}, Tracking a small set of experts by mixing past posteriors, 31-47 [Zbl 0992.68110] \textit{Cesa-Bianchi, Nicolò; Lugosi, Gábor}, Potential-based algorithms in online prediction and game theory, 48-64 [Zbl 0992.68105] \textit{Zhang, Tong}, A sequential approximation bound for some sample-dependent convex optimization problems with applications in learning, 65-81 [Zbl 0998.68071] \textit{Chawla, Deepak; Li, Lin; Scott, Stephen}, Efficiently approximating weighted sums with exponentially many terms, 82-98 [Zbl 0992.68092] \textit{Crammer, Koby; Singer, Yoram}, Ultraconservative online algorithms for multiclass problems, 99-115 [Zbl 0992.68111] \textit{Goldberg, Paul W.}, Estimating a Boolean perceptron from its average satisfying assignment: A bound on the precision required, 116-127 [Zbl 0998.68070] \textit{Mannor, Shie; Shimkin, Nahum}, Adaptive strategies and regret minimization in arbitrarily varying Markov environments, 128-142 [Zbl 0992.68115] \textit{Case, John; Jain, Sanjay; Stephan, Frank; Wiehagen, Rolf}, Robust learning -- rich and poor, 143-159 [Zbl 0992.68108] \textit{Zilles, Sandra}, On the synthesis of strategies identifying recursive functions, 160-176 [Zbl 0992.68101] \textit{Jain, Sanjay; Kinber, Efim}, Intrinsic complexity of learning geometrical concepts from positive data, 177-193 [Zbl 0992.68096] \textit{Stork, David G.}, Toward a computational theory of data acquisition and truthing, 194-207 [Zbl 0992.68510] \textit{Piccolboni, Antonio; Schindelhauer, Christian}, Discrete prediction games with arbitrary feedback and loss. (Extended abstract), 208-223 [Zbl 0992.68506] \textit{Bartlett, Peter L.; Mendelson, Shahar}, Rademacher and Gaussian complexities: Risk bounds and structural results, 224-240 [Zbl 0992.68106] \textit{Koltchinskii, Vladimir; Panchenko, Dmitriy; Lozano, Fernando}, Further explanation of the effectiveness of voting methods: The game between margins and weights, 241-255 [Zbl 0992.68511] \textit{Mendelson, Shahar}, Geometric methods in the analysis of Glivenko-Cantelli classes, 256-272 [Zbl 0992.68094] \textit{Mendelson, Shahar}, Learning relatively small classes, 273-288 [Zbl 0998.68068] \textit{Long, Philip M.}, On agnostic learning with \(\{0, *, 1\}\)-valued and real-valued hypotheses, 289-302 [Zbl 0992.68099] \textit{Goldberg, Paul W.}, When can two unsupervised learners achieve PAC separation?, 303-319 [Zbl 0992.68112] \textit{Grünwald, Peter}, Strong entropy concentration, game theory, and algorithmic randomness, 320-336 [Zbl 0992.68109] \textit{Nouretdinov, Ilia; Vovk, Volodya; Vyugin, Michael; Gammerman, Alex}, Pattern recognition and density estimation under the general i. i. d. assumption, 337-353 [Zbl 0992.68104] \textit{Balcázar, José L.; Castro, Jorge; Guijarro, David}, A general dimension for exact learning, 354-367 [Zbl 0992.68087] \textit{Kégl, Balázs; Linder, Tamás; Lugosi, Gábor}, Data-dependent margin-based generalization bounds for classification, 368-384 [Zbl 0992.68091] \textit{Ben-David, Shai; Eiron, Nadav; Simon, Hans Ulrich}, Limitations of learning via embeddings in Euclidean half-spaces, 385-401 [Zbl 0998.68069] \textit{Forster, Jürgen; Schmitt, Niels; Simon, Hans Ulrich}, Estimating the optimal margins of embeddings in Euclidean half spaces, 402-415 [Zbl 0998.68067] \textit{Schölkopf, Bernhard; Herbrich, Ralf; Smola, Alex J.}, A generalized representer theorem, 416-426 [Zbl 0992.68088] \textit{Zhang, Tong}, A leave-one-out cross validation bound for kernel methods with applications in learning, 427-443 [Zbl 0992.68113] \textit{Herbster, Mark}, Learning additive models online with fast evaluating kernels, 444-460 [Zbl 0992.68507] \textit{Mannor, Shie; Meir, Ron}, Geometric bounds for generalization in boosting, 461-472 [Zbl 0992.68093] \textit{Servedio, Rocco A.}, Smooth boosting and learning with malicious noise, 473-489 [Zbl 0992.68509] \textit{Bshouty, Nader H.; Gavinsky, Dmitry}, On boosting with optimal poly-bounded distributions, 490-506 [Zbl 0992.68508] \textit{Ben-David, Shai; Long, Philip M.; Mansour, Yishay}, Agnostic boosting, 507-516 [Zbl 0992.68089] \textit{Lee, Wee Sun; Long, Philip M.}, A theoretical analysis of query selection for collaborative filtering, 517-528 [Zbl 0992.68505] \textit{Bshouty, Nader H.; Feldman, Vitaly}, On using extended statistical queries to avoid membership queries, 529-545 [Zbl 0992.68102] \textit{Bshouty, Nader H.; Eiron, Nadav}, Learning monotone DNF from a teacher that almost does not answer membership queries, 546-557 [Zbl 0992.68114] \textit{Servedio, Rocco A.}, On learning monotone DNF under product distributions, 558-573 [Zbl 0992.68100] \textit{Bshouty, Nader; Owshanko, Avi}, Learning regular sets with an incomplete membership oracle, 574-588 [Zbl 0992.68098] \textit{Even-Dar, Eyal; Mansour, Yishay}, Learning rates for Q-learning, 589-604 [Zbl 0992.68097] \textit{Kakade, Sham}, Optimizing average reward using discounted rewards, 605-615 [Zbl 0992.68103] \textit{Peshkin, Leonid; Mukherjee, Sayan}, Bounds on sample size for policy evaluation in Markov environments, 616-629 [Zbl 0992.68090]