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32nd International Conference on Machine Learning (ICML 2015)
Bach, Francis [szerk.]
;
Blei, David [szerk.]
Angol nyelvű Konferenciakötet (Könyv) Tudományos
Megjelent: International Machine Learning Society (IMLS), Stroudsburg, Amerikai Egyesült Államok
2015
Konferencia:
32nd International Conference on Machine Learning 2015-07-06 [Lille, Franciaország]
Sorozatok:
Proceedings of Machine Learning Research 2640-3498, 37
Azonosítók
MTMT: 33369477
ISBN:
9781510810587
Teljes dokumentum:
https://proceedings.mlr.press/v37/
Fejezetek
Ahn K J et al. Correlation clustering in data streams. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015)
Zhao Peilin et al. Stochastic Optimization with Importance Sampling for Regularized Loss Minimization. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 1-9
Bounliphone W et al. A low variance consistent test of relative dependency. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 20-29
Ma Z et al. Finding linear structure in large datasets with scalable canonical correlation analysis. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 169-178
Kandasamy K. et al. High dimensional Bayesian Optimisation and bandits via additive models. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 295-304
Hocking Toby Dylan et al. PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 324-332
Zhang Yuchen et al. Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 353-361
Zhang Yuchen et al. DiSCO: Distributed Optimization for Self-Concordant Empirical Loss. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 362-370
Ioffe S. et al. Batch normalization: Accelerating deep network training by reducing internal covariate shift. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 448-456
Yang Wenzhuo et al. A Unified Framework for Outlier-Robust PCA-like Algorithms. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 484-493
Yang Wenzhuo et al. Streaming Sparse Principal Component Analysis. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 494-503
Garber Dan et al. Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 541-549
Csiba Dominik et al. Stochastic Dual Coordinate Ascent with Adaptive Probabilities. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 674-683
Ene Alina et al. Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 787-795
Krichene Walid et al. The Hedge Algorithm on a Continuum. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 824-832
Sun Tao et al. Message Passing for Collective Graphical Models. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 853-861
Cohen A. et al. Following the Perturbed Leader for online structured learning. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 1034-1042
Wu Y. et al. On identifying good options under combinatorially structured feedback in finite noisy environments. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 1283-1291
Miyauchi A. et al. Threshold influence model for allocating advertising budgets. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 1395-1404
Tagorti Manel et al. On the Rate of Convergence and Error Bounds for LSTD(lambda). (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 1521-1529
Ciliberto Carlo et al. Convex Learning of Multiple Tasks and their Structure. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 1548-1557
Lesner B et al. Non-stationary approximate modified policy iteration. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 1567-1575
Nutini Julie et al. Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 1632-1641
Van Seijen H. et al. A deeper look at planning as learning from replay. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 2304-2312
Hsieh Cho-Jui et al. PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 2370-2379
Mariet Z et al. Fixed-point algorithms for learning determinantal point processes. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 2379-2387
Aybat N. S. et al. An Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization. (2015) Megjelent: 32nd International Conference on Machine Learning (ICML 2015) pp. 2454-2462
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