Found 174 Documents (Results 1–100)
Specifying and solving robust empirical risk minimization problems using CVXPY. (English) Zbl 07922479
Constructing decision rules for multiproduct newsvendors: an integrated estimation-and-optimization framework. (English) Zbl 07895436
MSC:
90Bxx
Using Taylor-approximated gradients to improve the Frank-Wolfe method for empirical risk minimization. (English) Zbl 07887989
Stochastic three-term conjugate gradient method with variance technique for non-convex learning. (English) Zbl 1541.62018
Finding the optimal dynamic treatment regimes using smooth Fisher consistent surrogate loss. (English) Zbl 1539.62322
Gradient complexity and non-stationary views of differentially private empirical risk minimization. (English) Zbl 07809106
MSC:
68Qxx
Nonexact oracle inequalities, \(r\)-learnability, and fast rates. (English) Zbl 1537.62019
Reviewer: Fabio Rapallo (Alessandria)
Accelerated stochastic Peaceman-Rachford method for empirical risk minimization. (English) Zbl 07802576
A mini-batch stochastic conjugate gradient algorithm with variance reduction. (English) Zbl 1528.90191
Nonconvex optimization with inertial proximal stochastic variance reduction gradient. (English) Zbl 1533.90085
Neural network approximation and estimation of classifiers with classification boundary in a Barron class. (English) Zbl 1538.68037
Bayesian inference for risk minimization via exponentially tilted empirical likelihood. (English) Zbl 07909614
MSC:
62-XX
Direct Gibbs posterior inference on risk minimizers: construction, concentration, and calibration. (English) Zbl 1539.62069
Rao, Arni S. R. Srinivasa (ed.) et al., Advancements in Bayesian methods and implementations. Amsterdam: Elsevier/Academic Press. Handb. Stat. 47, 1-41 (2022).
Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization. (English) Zbl 1530.90061
Stochastic approximation versus sample average approximation for Wasserstein barycenters. (English) Zbl 1517.90088
Global convergence of stochastic gradient Hamiltonian Monte Carlo for nonconvex stochastic optimization: nonasymptotic performance bounds and momentum-based acceleration. (English) Zbl 1508.90039
Joint feature selection and classification for positive unlabelled multi-label data using weighted penalized empirical risk minimization. (English) Zbl 07568660
A novel adaptive differential privacy algorithm for empirical risk minimization. (English) Zbl 1481.90208
Elicitation complexity of statistical properties. (English) Zbl 07459737
MSC:
62-XX
Empirical risk minimization for dynamical systems and stationary processes. (English) Zbl 07446779
MSC:
62Mxx
Set structured global empirical risk minimizers are rate optimal in general dimensions. (English) Zbl 1478.62081
Concentration inequalities for two-sample rank processes with application to bipartite ranking. (English) Zbl 1471.62356
Non-convergence of stochastic gradient descent in the training of deep neural networks. (English) Zbl 1494.65044
Stochastic variance reduced gradient methods using a trust-region-like scheme. (English) Zbl 1461.90071
A maximum principle argument for the uniform convergence of graph Laplacian regressors. (English) Zbl 1485.35137
Analysis of the generalization error: empirical risk minimization over deep artificial neural networks overcomes the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations. (English) Zbl 1480.60191
Robust 1-bit compressed sensing via hinge loss minimization. (English) Zbl 1470.94041
Inf. Inference 9, No. 2, 361-422 (2020); erratum ibid. 9, No. 2, 505-506 (2020).
Empirical risk minimization in the non-interactive local model of differential privacy. (English) Zbl 1541.68131
Empirical risk minimization and complexity of dynamical models. (English) Zbl 1459.62165
Reviewer: Claudia Simionescu-Badea (Wien)
Accelerated dual-averaging primal-dual method for composite convex minimization. (English) Zbl 1454.90059
MSC:
90C25
Distributed block-diagonal approximation methods for regularized empirical risk minimization. (English) Zbl 1496.68276
Empirical risk minimization: probabilistic complexity and stepsize strategy. (English) Zbl 1422.90036
MSC:
90C25
Utilizing second order information in minibatch stochastic variance reduced proximal iterations. (English) Zbl 1487.90529
Compactness hypothesis, potential functions, and rectifying linear space in machine learning. (English) Zbl 1518.68316
Rozonoer, Lev (ed.) et al., Braverman readings in machine learning. Key ideas from inception to current state. International conference commemorating the 40th anniversary of Emmanuil Braverman’s decease, Boston, MA, USA, April 28–30, 2017. Invited talks. Cham: Springer. Lect. Notes Comput. Sci. 11100, 52-102 (2018).
Combinatorial bounds of overfitting for threshold classifiers. (Russian. English summary) Zbl 1463.68053
Ufim. Mat. Zh. 10, No. 1, 50-65 (2018); translation in Ufa Math. J. 10, No. 1, 49-63 (2018).
Key theorem of learning theory with samples corrupted by noise on chance space. (Chinese. English summary) Zbl 1424.68118
MSC:
68T05
Communication-efficient distributed optimization of self-concordant empirical loss. (English) Zbl 1412.90118
Giselsson, Pontus (ed.) et al., Large-scale and distributed optimization. Contributions of the workshop, Lund, Sweden, June 14–16, 2017. Cham: Springer. Lect. Notes Math. 2227, 289-341 (2018).
Who should be treated? Empirical welfare maximization methods for treatment choice. (English) Zbl 1419.91280
Coordinate descent faceoff: primal or dual? (English) Zbl 1405.68284
Janoos, Firdaus (ed.) et al., Algorithmic learning theory 2018. Proceedings of the 29th international conference (ALT 2018), Lanzarote, Spain, April 7–9, 2018. [s.l.]: Proceedings of Machine Learning Research PMLR. Proceedings of Machine Learning Research (PMLR) 83, 246-267 (2018).
Ranking median regression: learning to order through local consensus. (English) Zbl 1405.68282
Janoos, Firdaus (ed.) et al., Algorithmic learning theory 2018. Proceedings of the 29th international conference (ALT 2018), Lanzarote, Spain, April 7–9, 2018. [s.l.]: Proceedings of Machine Learning Research PMLR. Proceedings of Machine Learning Research (PMLR) 83, 212-245 (2018).
High-dimensional penalty selection via minimum description length principle. (English) Zbl 1477.62137
Importance sampling for minibatches. (English) Zbl 06982318
MSC:
65C60
The landscape of empirical risk for nonconvex losses. (English) Zbl 1409.62117
Reviewer: Rózsa Horváth-Bokor (Budakalász)
Robust low-rank matrix estimation. (English) Zbl 1412.62068
Reviewer: Wolfgang Näther (Freiberg)
Parallel and robust empirical risk minimization via the median trick. (English) Zbl 1497.68427
Blömer, Johannes (ed.) et al., Mathematical aspects of computer and information sciences. 7th international conference, MACIS 2017, Vienna, Austria, November 15–17, 2017. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 10693, 378-391 (2017).
Stochastic primal-dual coordinate method for regularized empirical risk minimization. (English) Zbl 1440.62314
A new analytical approach to consistency and overfitting in regularized empirical risk minimization. (English) Zbl 1383.49029
Inexact proximal stochastic gradient method for convex composite optimization. (English) Zbl 1390.90432
On the principle of empirical risk minimization based on averaging aggregation functions. (English. Russian original) Zbl 1392.62084
Dokl. Math. 96, No. 2, 494-497 (2017); translation from Dokl. Akad. Nauk, Ross. Akad. Nauk 476, No. 5, 495-499 (2017).
Rejoinder. (English) Zbl 1380.62086
Discussion of the paper “On concentration for (regularized) empirical risk minimization”. (English) Zbl 1380.62078
MSC:
62E20
Proximal average approximated incremental gradient descent for composite penalty regularized empirical risk minimization. (English) Zbl 1459.62156
Bounds on the rate of uniform convergence of learning process based on fuzzy random samples. (Chinese. English summary) Zbl 1389.68072
MSC:
68T05
The key theorem of learning theory based on quasi-probability and fuzzy samples. (Chinese. English summary) Zbl 1389.68066
MSC:
68T05
Localization of VC classes: beyond local Rademacher complexities. (English) Zbl 1398.68472
Ortner, Ronald (ed.) et al., Algorithmic learning theory. 27th international conference, ALT 2016, Bari, Italy, October 19–21, 2016, Proceedings. Cham: Springer (ISBN 978-3-319-46378-0/pbk; 978-3-319-46379-7/ebook). Lecture Notes in Computer Science 9925. Lecture Notes in Artificial Intelligence, 18-33 (2016).
Convergence and consistency of ERM algorithm with uniformly ergodic Markov chain samples. (English) Zbl 1341.60089
Scaling-up empirical risk minimization: optimization of incomplete \(U\)-statistics. (English) Zbl 1360.62173
Empirical risk minimization for variable consistency dominance-based rough set approach. (English) Zbl 1444.68216
Yao, Yiyu (ed.) et al., Rough sets, fuzzy sets, data mining, and granular computing. 15th international conference, RSFDGrC 2015, Tianjin, China, November 20–23, 2015. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 9437, 63-72 (2015).
MSC:
68T37
Key theorem of learning theory with samples corrupted by noise on quasi-probability space. (Chinese. English summary) Zbl 1349.68141
MSC:
68T05
Learning without concentration. (English) Zbl 1333.68232
MSC:
68T05
Batch learning from logged bandit feedback through counterfactual risk minimization. (English) Zbl 1351.68236
Models for optimization of power systems. (English) Zbl 1332.90127
Al-Baali, Mehiddin (ed.) et al., Numerical analysis and optimization. Selected papers based on the presentations at the 3rd international conference, NAO-III, Muscat, Oman, January 5–9, 2014. Cham: Springer (ISBN 978-3-319-17688-8/hbk; 978-3-319-17689-5/ebook). Springer Proceedings in Mathematics & Statistics 134, 289-317 (2015).
Distributed block coordinate descent for minimizing partially separable functions. (English) Zbl 1330.65089
Al-Baali, Mehiddin (ed.) et al., Numerical analysis and optimization. Selected papers based on the presentations at the 3rd international conference, NAO-III, Muscat, Oman, January 5–9, 2014. Cham: Springer (ISBN 978-3-319-17688-8/hbk; 978-3-319-17689-5/ebook). Springer Proceedings in Mathematics & Statistics 134, 261-288 (2015).
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