Group: Statistical Machine Learning - library 168 articles Export

	Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results [My Copy] Journal of Machine Learning Research, Vol. 8 (April 2007), pp. 775-790. by Peter L. Bartlett, Ambuj Tewari posted to sparse probability estimation consistency asymptotic_results by mdreid to the group Statistical Machine Learning on 2009-10-12 02:25:17 as
	Coherence functions for multicategory margin-based classification methods. [My Copy] In Proceedings of the Twelfth Conference on Artificial Intelligence and Statistics (AISTATS) (2009) by Z. Zhang, M. I. Jordan, W. J. Li, D. Y. Yeung posted to theory surrogate multiclass margin convexity consistency boosting by mdreid to the group Statistical Machine Learning on 2009-09-17 09:17:15 as
	Stochastic methods for <i>l</i><sub>1</sub> regularized loss minimization [My Copy] In ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 929-936. by Shai S. Shwartz, Ambuj Tewari posted to sgd scd regularisation online l1 by mdreid to the group Statistical Machine Learning on 2009-09-01 08:19:33 as
	New multicategory boosting algorithms based on multicategory Fisher-consistent losses [My Copy] The Annals of Applied Statistics, Vol. 2, No. 4. (December 2008), pp. 1290-1306. by Hui Zou, Ji Zhu, Trevor Hastie posted to multiclass consistency boosting algorithm by mdreid to the group Statistical Machine Learning on 2009-08-24 04:54:12 as
	Eliciting Truthful Answers to Multiple-Choice Questions [My Copy] In 10th ACM Conference on Electronic Commerce (2009) by Nicolas Lambert, Yoav Shoham posted to distributions elicitation scoring_rules by mdreid to the group Statistical Machine Learning on 2009-07-13 03:56:10 as
	Stochastic Convex Optimization [My Copy] In Proceedings of the Conference on Learning Theory (COLT) (2009) by Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan posted to consistency on-line regularisation theory by mdreid to the group Statistical Machine Learning on 2009-07-08 03:55:09 as along with 1 person Vezhnick
	On the efficient minimization of convex surrogates in supervised learning [My Copy] Pattern Recognition, 2008. ICPR 2008. 19th International Conference on In Pattern Recognition, 2008. ICPR 2008. 19th International Conference on (2008), pp. 1-4. by R. Nock, F. Nielseny posted to boosting bounds scoring_rules surrogate_loss theory by mdreid to the group Statistical Machine Learning on 2009-05-17 01:42:38 as
	An Improved Predictive Accuracy Bound for Averaging Classifiers [My Copy] In ICML '01: Proceedings of the Eighteenth International Conference on Machine Learning (2001), pp. 290-297. by John Langford, Matthias Seeger, Nimrod Megiddo posted to bounds classification margin pac-bayes theory by mdreid to the group Statistical Machine Learning on 2009-04-08 12:32:59 as
	A Stochastic View of Optimal Regret through Minimax Duality [My Copy] (30 Mar 2009) by Jacob Abernethy, Alekh Agarwal, Peter L. Bartlett, Alexander Rakhlin posted to bregman_divergence convexity duality game_theory on-line by mdreid to the group Statistical Machine Learning on 2009-04-01 09:03:20 as
	Evidence Contrary to the Statistical View of Boosting [My Copy] Journal of Machine Learning Research, Vol. 9 (February 2008), pp. 131-156. by David Mease, Abraham Wyner posted to boosting estimation evaluation experimental survey by mdreid to the group Statistical Machine Learning on 2009-03-26 01:55:37 as along with 3 people ptrobajo sdvillal jjrodriguez
	The Tradeoffs of Large Scale Learning [My Copy] In Advances in Neural Information Processing Systems 20 (2008), pp. 161-168. by Léon Bottou, Olivier Bousquet edited by J. C. Platt, D. Koller, Y. Singer, S. Roweis posted to large_scale on-line stochastic_gradient_descent surrogate_loss by mdreid to the group Statistical Machine Learning on 2009-03-22 09:53:51 as
	Statistical Learning Theory: Models, Concepts, and Results [My Copy] (27 Oct 2008) by Ulrike von Luxburg, Bernhard Schoelkopf posted to inequality learning survey theory tutorial by mdreid to the group Statistical Machine Learning on 2009-03-16 06:19:40 as along with 4 people arsyed ansobol dah robotact
	On surrogate loss functions and f-divergences [My Copy] Annals of Statistics, Vol. 37, No. 2. (2009), pp. 876-904. by Xuanlong Nguyen, Martin J. Waonwright, Michael I. Jordan posted to f-divergence quantisation surrogate_loss by mdreid to the group Statistical Machine Learning on 2009-03-10 23:08:48 as
	Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics [My Copy] In SLS 2007, Vol. 4638 (6--8 September 2007) edited by Thomas Stützle, Mauro Birattari, Holger H. Hoos posted to algorithm-engineering experimental metaheuristic parameter-setting performance-assessment stochastic stochastic-local-search by nojhan to the group Statistical Machine Learning on 2008-11-07 09:19:46 as along with 3 groups Optimization Metaheuristics EvolutionaryComputation
	Combinatorial Information Market Design [My Copy] Information Systems Frontiers (January 2003), pp. 107-119. by R. Hanson posted to prediction_markets scoring_rules by mdreid to the group Statistical Machine Learning on 2008-08-07 01:06:05 as
	ECONOMICS: The Promise of Prediction Markets [My Copy] Science, Vol. 320, No. 5878. (16 May 2008), pp. 877-878. by Kenneth J. Arrow, Robert Forsythe, Michael Gorham, et al.Robert Hahn, Robin Hanson, John O. Ledyard, Saul Levmore, Robert Litan, Paul Milgrom, Forrest D. Nelson, George R. Neumann, Marco Ottaviani, Thomas C. Schelling, Robert J. Shiller, Vernon L. Smith, Erik Snowberg, Cass R. Sunstein, Paul C. Tetlock, Philip E. Tetlock, Hal R. Varian, Justin Wolfers, Eric Zitzewitz posted to economics politics prediction_markets by mdreid to the group Statistical Machine Learning on 2008-07-29 00:53:15 as along with 3 people mimo jago stringertheory
	Graphical models, exponential families, and variational inference [My Copy] (17 September 2003) by Martin J. Wainwright, Michael I. Jordan posted to duality by mdreid to the group Statistical Machine Learning on 2008-07-11 17:51:11 as along with 1 person tdhollan
	Unifying Divergence Minimization and Statistical Inference Via Convex Duality [My Copy] Learning Theory (2006), pp. 139-153. by Yasemin Altun, Alex Smola posted to class_probability_estimation convexity divergence duality exponential_family by mdreid to the group Statistical Machine Learning on 2008-05-28 07:48:54 as
	A class of logistic-type discriminant functions [My Copy] Biometrika, Vol. 89, No. 1. (1 March 2002), pp. 1-22. by Shinto Eguchi, John Copas posted to auc classification class_probability_estimation logistic loss neyman-pearson roc weighting by mdreid to the group Statistical Machine Learning on 2008-04-30 06:53:15 as
	Cost curves: An improved method for visualizing classifier performance [My Copy] Machine Learning, Vol. 65, No. 1. (October 2006), pp. 95-130. by Drummond, Chris, Holte, Robert posted to auc classification evaluation roc visualization by mdreid to the group Statistical Machine Learning on 2008-03-14 04:43:53 as along with 2 people tubbens justintalbot
	Considering Cost Asymmetry in Learning Classifiers [My Copy] Journal of Machine Learning Research, Vol. 7 (August 2006), pp. 1713-1741. by Francis R. Bach, David Heckerman, Eric Horvitz posted to auc classification cost_sensitive roc svm by mdreid to the group Statistical Machine Learning on 2008-03-14 04:41:57 as
	On Divergences and Informations in Statistics and Information Theory [My Copy] Information Theory, IEEE Transactions on In Information Theory, IEEE Transactions on, Vol. 52, No. 10. (2006), pp. 4394-4412. by F. Liese, I. Vajda posted to f-divergence statistical_information by mdreid to the group Statistical Machine Learning on 2008-01-15 04:50:55 as along with 1 person memming
	The geometry of proper scoring rules [My Copy] Annals of the Institute of Statistical Mathematics, Vol. 59, No. 1. (17 March 2007), pp. 77-93. by A. Dawid posted to theory scoring_rules information_geometry geometry convexity by mdreid to the group Statistical Machine Learning on 2009-10-22 00:24:13 as
	Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary β-Mixing Processes [My Copy] (10 Sep 2009) by Liva Ralaivola, Marie Szafranski, Guillaume Stempfel posted to theory ranking pac-bayes bounds by mdreid to the group Statistical Machine Learning on 2009-09-14 00:49:33 as
	Robustness and Regularization of Support Vector Machines [My Copy] Journal of Machine Learning Research, Vol. 10 (July 2009), pp. 1485-1510. by Huan Xu, Constantine Caramanis, Shie Mannor posted to theory svm stability robustness regularisation by mdreid to the group Statistical Machine Learning on 2009-08-12 08:13:19 as along with 1 person shivak
	Random classification noise defeats all convex potential boosters [My Copy] In ICML, Vol. 307 (2008), pp. 608-615. by Philip M. Long, Rocco A. Servedio edited by William W. Cohen, Andrew Mccallum, Sam T. Roweis, William W. Cohen, Andrew Mccallum, Sam T. Roweis posted to boosting robustness theory by mdreid to the group Statistical Machine Learning on 2009-05-15 08:22:26 as
	A more robust boosting algorithm [My Copy] (13 May 2009) by Yoav Freund posted to boosting convexity margin robustness by mdreid to the group Statistical Machine Learning on 2009-05-15 08:19:34 as along with 2 people jjrodriguez shivak
	On Uniform Deviations of General Empirical Risks with Unboundedness, Dependence, and High Dimensionality [My Copy] Journal of Machine Learning Research, Vol. 10 (April 2009), pp. 977-996. by Wenxin Jiang posted to bounds erm loss theory by mdreid to the group Statistical Machine Learning on 2009-05-04 01:14:20 as along with 1 person shivak
	Consistency and Localizability [My Copy] Journal of Machine Learning Research, Vol. 10 (April 2009), pp. 827-856. by Alon Zakai, Ya'acov Ritov posted to consistency svm theory by mdreid to the group Statistical Machine Learning on 2009-05-03 23:33:52 as along with 2 people shivak sdvillal
	Introduction to Statistical Learning Theory [My Copy] In Advanced Lectures on Machine Learning, Vol. 3176 (2004), pp. 169-207. by Olivier Bousquet, Stéphane Boucheron, Gábor Lugosi posted to bounds survey theory by mdreid to the group Statistical Machine Learning on 2009-04-11 03:16:59 as
	Prediction with expert evaluators' advice [My Copy] (23 Mar 2009) by Alexey Chernov, Vladimir Vovk posted to algorithm experts loss on-line protocol by mdreid to the group Statistical Machine Learning on 2009-03-24 03:42:28 as
	Maximum Entropy Discrimination Markov Networks [My Copy] (18 Jan 2009) by Jun Zhu, Eric P. Xing posted to bayesian discriminative generative max-ent max-margin by mdreid to the group Statistical Machine Learning on 2009-03-16 06:22:06 as
	Challenges in Statistical Machine Learning [My Copy] Statistica Sinica, Vol. 16 (2006), pp. 307-322. by John Lafferty, Larry Wasserman posted to dimensional_reduction prediction risk semisupervised structure survey theory by mdreid to the group Statistical Machine Learning on 2009-03-12 08:07:13 as
	Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization [My Copy] Advances in Computational Mathematics, Vol. 25, No. 1-3. (July 2006), pp. 161-193. by Mukherjee, Sayan, Niyogi, et al. Partha, Poggio, Tomaso, Rifkin, Ryan posted to consistency erm learning stability theory by mdreid to the group Statistical Machine Learning on 2009-02-10 22:18:46 as along with 1 person NicolaSegata
	Relations among conditional probabilities [My Copy] (8 Aug 2008) by Jason Morton posted to algebraic discrete probability statistics theory by mdreid to the group Statistical Machine Learning on 2009-01-17 02:50:30 as along with 2 people algorithmic jleny
	Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection [My Copy] J. Mach. Learn. Res., Vol. 6 (2005), pp. 995-1018. by Koji Tsuda, Gunnar Rätsch, Manfred K. Warmuth posted to bregman_divergence gradient matrix on-line by mdreid to the group Statistical Machine Learning on 2009-01-12 21:02:13 as along with 1 person and 1 group ciga Computational_Information_Geometry
	L1-regularization path algorithm for generalized linear models [My Copy] Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 69, No. 4. (September 2007), pp. 659-677. by Park, Mee Young, Hastie, Trevor posted to lasso regularization by cyberwulf to the group Statistical Machine Learning on 2008-12-29 20:46:16 as
	Linkage in Evolutionary Computation [My Copy] Vol. 157 (2008) edited by Ying-Ping Chen, Meng-Hiot Lim posted to estimation-of-distribution-algorithm evolutionary-computation linkage metaheuristic multivariate by nojhan to the group Statistical Machine Learning on 2008-12-08 15:53:44 as along with 1 person and 2 groups oskenund Metaheuristics EvolutionaryComputation
	Measures of Clustering Quality: A Working Set of Axioms for Clustering [My Copy] In Proceedings of the 22nd Annual Conference on Neural Information Systems Processing (2008) by Margareta Ackerman, Shai Ben-David posted to clustering by mdreid to the group Statistical Machine Learning on 2008-11-24 00:17:36 as along with 2 people shpigi arsyed
	Support Vector Machines [My Copy] (2008) by Ingo Steinwart, Andreas Christmann posted to no-tag by mdreid to the group Statistical Machine Learning on 2008-09-15 07:18:41 as along with 1 person jorgeac
	Convex solutions of a functional equation arising in information theory [My Copy] Journal of Mathematical Analysis and Applications, Vol. 328, No. 2. (15 April 2007), pp. 1309-1320. by J. B. Hiriart-Urruty, J. E. Martínez-Legaz posted to convexity f-divergence information theory by mdreid to the group Statistical Machine Learning on 2008-09-05 06:00:59 as
	Structured machine learning: the next ten years [My Copy] Machine Learning by Thomas Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, Prasad Tadepalli posted to future structure survey by mdreid to the group Statistical Machine Learning on 2008-09-03 03:28:37 as along with 8 people jjrodriguez abvg sona danielkcook bcao EmreSevinc briordan AbnerCYH
	Persistent Clustering and a Theorem of J. Kleinberg [My Copy] (16 Aug 2008) by Gunnar Carlsson, Facundo Memoli posted to category_theory clustering theory trees by mdreid to the group Statistical Machine Learning on 2008-08-27 09:13:54 as along with 1 person leemond31
	Scoring rules and the evaluation of probabilities [My Copy] TEST, Vol. 5, No. 1. (28 March 1990), pp. 1-60. by R. Winkler, Javier Muñoz, José Cervera, et al.José Bernardo, Gail Blattenberger, Joseph Kadane, Dennis Lindley, Allan Murphy, Robert Oliver, David Ríos-Insua posted to probability scoring_rules by mdreid to the group Statistical Machine Learning on 2008-07-22 00:23:11 as
	An Augmented PAC Model for Semi-Supervised Learning [My Copy] In Semi-Supervised Learning (2006), pp. 397-420. by Maria-Florina Balcan, Avrim Blum edited by Olivier Chapelle, Bernhard Schölkopf, Alexander Zien posted to bounds compatibility pac semisupervised theory by mdreid to the group Statistical Machine Learning on 2008-07-21 06:31:07 as along with 1 person deysandeep
	Kernel methods in machine learning [My Copy] Annals of Statistics, Vol. 36, No. 3. (2008), pp. 1171-1220. by Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola posted to kernel svm by mdreid to the group Statistical Machine Learning on 2008-07-21 00:07:43 as along with 2 people vlachmore tdhollan
	Local Rademacher complexities [My Copy] Annals of Statistics, Vol. 33, No. 4. (2005), pp. 1497-1537. by Peter L. Bartlett, Olivier Bousquet, Shahar Mendelson posted to bounds complexity data_dependent error inequality by mdreid to the group Statistical Machine Learning on 2008-07-18 02:52:53 as along with 1 person davidr
	Deconstructing Statistical Questions [My Copy] Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 157, No. 3. (1994), pp. 317-356. by David J. Hand posted to methodology philosophy statistics theory by mdreid to the group Statistical Machine Learning on 2008-06-25 07:09:48 as
	On the Theory of Scales of Measurement [My Copy] by S. S. Stevens posted to historical measurement theory by mdreid to the group Statistical Machine Learning on 2008-06-24 05:53:10 as along with 3 people and 1 group breyten peefeeyatko rrbarb ilps
	Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data [My Copy] In Proc. 18th International Conf. on Machine Learning (2001), pp. 282-289. by John Lafferty, Andrew Mccallum, Fernando Pereira posted to crf learning machine markov models statistical by jmackay to the group Statistical Machine Learning on 2008-05-07 08:51:12 as along with 26 people and 3 groups kabus pprett ttylenda jkominek krisl mehrbod davidr halacsy unnonouno balajis buescher76 wcohen sids j3xucite knmnyn student_t dwf bundschu johnkork koji_matsuda mkolar markusd vlachmore kohei-h oyen idornescu oktave-labs generif_paper WLV-RGCL

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theory	63
classification	21
bounds	19
convexity	17
probability	14
bayesian	12
scoring_rules	12
survey	11
boosting	10
information	10
auc	9
consistency	9
divergence	9
f-divergence	9
statistics	9
kernel	8
ranking	8
roc	8
bregman_divergence	7
dimensional_reduction	7
duality	7
erm	7
on-line	7
svm	7
class_probability_estimation	6
estimation	6
surrogate_loss	6
clustering	5
density_estimation	5
margin	5
metaheuristic	5
multiclass	5
online	5
regression	5
bregman	4
decision_theory	4
distributions	4
exponential_family	4
game_theory	4
inequality	4
information_geometry	4
learning	4
loss	4
max-ent	4
modelling	4
neyman-pearson	4
pac-bayes	4
pca	4
radamacher	4
regularisation	4
robustness	4
algebraic_geometry	3
algorithm	3
calibration	3
data	3
economics	3
ensemble	3
evaluation	3
graph_theory	3
large_scale	3
measurement	3
nonparametric	3
philosophy	3
prediction_markets	3
sparse	3
stacking	3
structure	3
weighting	3
application	2
category_theory	2
cca	2
collaborative_filtering	2
complexity	2
confidence	2
conformal_prediction	2
cost_sensitive	2
cross_language_document_retrieval	2
data_dependent	2
dc_program	2
embedding	2
evolutionary-computation	2
experimental	2
fda	2
generalized_eigenvalue_problem	2
global_convergence_analysis	2
graphical_models	2
historical	2
integral_representation	2
lecture_notes	2
logistic	2
machine-learning	2
majorization_minimization	2
markov	2
matrix	2
metric	2
mixture_models	2
music_annotation	2
networks	2
optimization	2
parameter-setting	2
protocol	2
random_projection	2
rates	2
reduction	2
representation	2
risk	2
semisupervised	2
sgd	2
software	2
spectral	2
stability	2
statistical_information	2
stochastic	2
trees	2
tutorial	2
algebraic	1
algorithm-engineering	1
asymmetric	1
asymptotic_results	1
auction	1
automata	1
axiomatic	1
bandit	1
c	1
chaining	1
characterisation	1
combinatorics	1
communication	1
compatibility	1
compiler	1
composition	1
compression	1
concentration	1
continuous	1
covariance	1
credibility	1
crf	1
criticism	1
data_mining	1
dirichlet_process	1
discrete	1
discretisation	1
discriminative	1
dynamic_programming	1
efficiency	1
eigenvector	1
elicitation	1
empiricism	1
energy-based-models	1
error	1
estimation-of-distribution-algorithm	1
exchangeability	1
expectation-maximization	1
experts	1
fenchel_duality	1
fisher_information	1
function_approximation	1
future	1
gaussian-mixture	1
generative	1
geometry	1
good-turing	1
gradient	1
grammars	1
graph	1
high-dimensional	1
history	1
hmm	1
hypothesis_testing	1
imbalance	1
induction	1
information_bottleneck	1
information_extraction	1
instance_weighting	1
interpretation	1
l1	1
language	1
lasso	1
linkage	1
machine	1
machine_learning	1
max-margin	1
methodology	1
mine	1
mixture	1
model	1
models	1
multivariate	1
noise	1
ockhams_razor	1
optimisation	1
pac	1
performance-assessment	1
phylogenetics	1
politics	1
popular_science	1
power	1
prediction	1
preference_elicitation	1
prior_selection	1
prob	1
projection	1
quantisation	1
queries	1
regularization	1
review	1
rkhs	1
scd	1
shanon-entropy	1
similarity	1
simplex	1
simplicity	1
srm	1
statistical	1
stochastic_gradient_descent	1
stochastic-local-search	1
stream	1
structure_learning	1
sufficiency	1
supervised	1
surrogate	1
topology	1
types	1
visual_grammars	1
visualization	1

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