Search results for "bias-variance"

Hits ?▲	Authors	Title	Venue	Year	Link	Author keywords
95	Giorgio Valentini	An experimental bias-variance analysis of SVM ensembles based on resampling techniques.	IEEE Trans. Syst. Man Cybern. Part B	2005	DBLP DOI BibTeX RDF
91	Meihong Zhu, Yong Shi 0001, Aihua Li, Peng Zhang 0001	A Bias-Variance Analysis of Multiple Criteria Linear Programming Classification Ensembles.	Web Intelligence/IAT Workshops	2008	DBLP DOI BibTeX RDF
79	Peter van der Putten, Maarten van Someren	A Bias-Variance Analysis of a Real World Learning Problem: The CoIL Challenge 2000.	Mach. Learn.	2004	DBLP DOI BibTeX RDF	bias-variance decomposition, real world applications, overfitting
78	Jakob Vogdrup Hansen, Tom Heskes	General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of Distributions.	ICPR	2000	DBLP DOI BibTeX RDF
75	Peng Zhang 0001, Xingquan Zhu 0001, Yong Shi 0001	Bias-Variance Analysis for Ensembling Regularized Multiple Criteria Linear Programming Models.	ICCS (2)	2009	DBLP DOI BibTeX RDF	Bias variance decomposition, RMCLP, Ensemble
73	Soummya Kar, José M. F. Moura	Distributed Consensus Algorithms in Sensor Networks With Imperfect Communication: Link Failures and Channel Noise.	IEEE Trans. Signal Process.	2009	DBLP DOI BibTeX RDF
64	Giorgio Valentini, Thomas G. Dietterich	Bias-Variance Analysis and Ensembles of SVM.	Multiple Classifier Systems	2002	DBLP DOI BibTeX RDF
63	M. Arthur Munson, Rich Caruana	On Feature Selection, Bias-Variance, and Bagging.	ECML/PKDD (2)	2009	DBLP DOI BibTeX RDF
60	V. Vijaya Saradhi, Harish Karnick	On the Stability and Bias-Variance Analysis of Kernel Matrix Learning.	Canadian AI	2007	DBLP DOI BibTeX RDF	Kernel matrix learning, bias-variance, stability, bootstrap, error estimation, overfitting
48	Remco R. Bouckaert	Practical Bias Variance Decomposition.	Australasian Conference on Artificial Intelligence	2008	DBLP DOI BibTeX RDF
47	Giorgio Valentini	Random Aggregated and Bagged Ensembles of SVMs: An Empirical Bias?Variance Analysis.	Multiple Classifier Systems	2004	DBLP DOI BibTeX RDF
42	Zhipeng Xie, Wynne Hsu, Mong-Li Lee	Mode Committee: A Novel Ensemble Method by Clustering and Local Learning.	ICTAI	2004	DBLP DOI BibTeX RDF
38	Raymond S. Smith, Terry Windeatt	The Bias Variance Trade-Off in Bootstrapped Error Correcting Output Code Ensembles.	MCS	2009	DBLP DOI BibTeX RDF
38	Jennifer Neville, David D. Jensen	A bias/variance decomposition for models using collective inference.	Mach. Learn.	2008	DBLP DOI BibTeX RDF	Evaluation, Statistical relational learning, Collective inference
38	Lean Yu, Kin Keung Lai, Shouyang Wang, Wei Huang 0006	A Bias-Variance-Complexity Trade-Off Framework for Complex System Modeling.	ICCSA (1)	2006	DBLP DOI BibTeX RDF
37	Francesco Gagliardi 0001	The Necessity of Machine Learning and Epistemology in the Development of Categorization Theories: A Case Study in Prototype-Exemplar Debate.	AI*IA	2009	DBLP DOI BibTeX RDF	Categorization Theories, Bias-Variance Dilemma, Machine Learning, Instance-Based Learning, Epistemology, Cognitive Psychology
37	Jérôme Boulanger, Charles Kervrann, Patrick Bouthemy	Space-Time Adaptation for Patch-Based Image Sequence Restoration.	IEEE Trans. Pattern Anal. Mach. Intell.	2007	DBLP DOI BibTeX RDF	Image sequence restoration, bias-variance trade-off, denoising, nonlinear filtering, nonparametric estimation
37	Silvia Riedel, Bogdan Gabrys	Combination of Multi Level Forecasts.	J. VLSI Signal Process.	2007	DBLP DOI BibTeX RDF	multi level forecasting, forecast combination, bias variance Bayes error decomposition, revenue management
37	Pierre Geurts, Damien Ernst, Louis Wehenkel	Extremely randomized trees.	Mach. Learn.	2006	DBLP DOI BibTeX RDF	Decision and regression trees, Cut-point randomization, Bias/variance tradeoff, Kernel-based models, Supervised learning, Ensemble methods
37	Yuk Lai Suen, Prem Melville, Raymond J. Mooney	Combining Bias and Variance Reduction Techniques for Regression Trees.	ECML	2005	DBLP DOI BibTeX RDF
37	Giorgio Valentini	An Application of Low Bias Bagged SVMs to the Classification of Heterogeneous Malignant Tissues.	WIRN	2003	DBLP DOI BibTeX RDF
35	David M. J. Tax, Klaus-Robert Müller	Feature Extraction for One-Class Classification.	ICANN	2003	DBLP DOI BibTeX RDF
31	Prasertsak Pungprasertying, Ratthachat Chatpatanasiri, Boonserm Kijsirikul	Migration Analysis: An Alternative Approach for Analyzing Learning Performance.	ICPR (2)	2006	DBLP DOI BibTeX RDF
27	Jennifer Neville, David D. Jensen	Bias/Variance Analysis for Relational Domains.	ILP	2007	DBLP DOI BibTeX RDF
27	Xiaojin Shi, Roberto Manduchi	Invariant Operators, Small Samples, and the Bias-Variance Dilemma.	CVPR (2)	2004	DBLP DOI BibTeX RDF
27	Mark Zlochin, Yoram Baram	The Bias-Variance Dilemma of the Monte Carlo Method.	ICANN	2001	DBLP DOI BibTeX RDF
27	Stijn Vanderlooy, Eyke Hüllermeier	A critical analysis of variants of the AUC.	Mach. Learn.	2008	DBLP DOI BibTeX RDF	Area under the ROC curve, Ranking performance, Bias-variance analysis, AUC variants, AUC maximization, ROC analysis
27	Charles Kervrann, Jérôme Boulanger	Local Adaptivity to Variable Smoothness for Exemplar-Based Image Regularization and Representation.	Int. J. Comput. Vis.	2008	DBLP DOI BibTeX RDF	Exemplar-based methods, Bias-variance trade-off, Bio-imaging, Estimation, Detection, Energy minimization, Restoration, Denoising, Nonlinear filtering
27	Yves Grandvalet	Bagging Equalizes Influence.	Mach. Learn.	2004	DBLP DOI BibTeX RDF	leverage, bias/variance, bagging, influence
27	Yi Zhang 0001	Using bayesian priors to combine classifiers for adaptive filtering.	SIGIR	2004	DBLP DOI BibTeX RDF	bias variance, information filtering, logistic regression
27	Deepak K. Agarwal	Shrinkage estimator generalizations of Proximal Support Vector Machines.	KDD	2002	DBLP DOI BibTeX RDF	bias-variance tradeoff, classification, correlation, regression, kernel, Bayesian models
27	S. V. Narasimhan, M. Harish, A. R. Haripriya, Nandini Basumallick	Discrete cosine harmonic wavelet transform and its application to signal compression and subband spectral estimation using modified group delay.	Signal Image Video Process.	2009	DBLP DOI BibTeX RDF	DCT harmonic wavelet transform, Signal and image compression, Subband spectral estimation and modified group delay
27	Steve Lawrence, C. Lee Giles	Overfitting and Neural Networks: Conjugate Gradient and Backpropagation.	IJCNN (1)	2000	DBLP DOI BibTeX RDF
21	Hui Li 0025, Juan Chen, Ying Tao, David L. Groep, Lex Wolters	Improving a Local Learning Technique for QueueWait Time Predictions.	CCGRID	2006	DBLP DOI BibTeX RDF
21	Juan José Rodríguez, Carlos J. Alonso, Oscar J. Prieto	Bias and Variance of Rotation-Based Ensembles.	IWANN	2005	DBLP DOI BibTeX RDF
21	Giorgio Fumera, Fabio Roli, Alessandra Serrau	Dynamics of Variance Reduction in Bagging and Other Techniques Based on Randomisation.	Multiple Classifier Systems	2005	DBLP DOI BibTeX RDF
21	João Gama 0001	Functional Trees.	Mach. Learn.	2004	DBLP DOI BibTeX RDF	multivariate decision trees, supervised learning, multiple models
21	Grigoris I. Karakoulas, Ruslan Salakhutdinov	Semi-Supervised Mixture-of-Experts Classification.	ICDM	2004	DBLP DOI BibTeX RDF
21	Andrew Skabar	Augmenting Supervised Neural Classifier Training Using a Corpus of Unlabeled Data.	KI	2002	DBLP DOI BibTeX RDF
21	Mehmet Yavuz, Jeffrey A. Fessler	New Statistical Models for Randoms-Precorrected PET Scans.	IPMI	1997	DBLP DOI BibTeX RDF
20	Evren Asma, Richard M. Leahy	Mean and covariance properties of dynamic PET reconstructions from list-mode data.	IEEE Trans. Medical Imaging	2006	DBLP DOI BibTeX RDF
17	Ossi Räisä, Antti Honkela	A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets.	CoRR	2024	DBLP DOI BibTeX RDF
17	Yurou Chen, Fengyi Zhang, Zhiyong Liu 0001	Adaptive bias-variance trade-off in advantage estimator for actor-critic algorithms.	Neural Networks	2024	DBLP DOI BibTeX RDF
17	Sanath Kumar Krishnamurthy, Adrienne M. Propp, Susan Athey	Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective.	AISTATS	2024	DBLP BibTeX RDF
17	Henry Lam, Haofeng Zhang	Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence.	J. Mach. Learn. Res.	2023	DBLP BibTeX RDF
17	Shayan Doroudi, Seyed Ali Rastegar	The Bias-Variance Tradeoff in Cognitive Science.	Cogn. Sci.	2023	DBLP DOI BibTeX RDF
17	Zheyuan Hu, Zhouhao Yang, Yezhen Wang, George Em Karniadakis, Kenji Kawaguchi	Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs.	CoRR	2023	DBLP DOI BibTeX RDF
17	Falaah Arif Khan, Julia Stoyanovich	The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction.	CoRR	2023	DBLP DOI BibTeX RDF
17	Sebastian G. Gruber, Florian Büttner	A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models.	CoRR	2023	DBLP DOI BibTeX RDF
17	Fangyuan Wang, Ming Hao, Yuhai Shi, Bo Xu 0002	ApproBiVT: Lead ASR Models to Generalize Better Using Approximated Bias-Variance Tradeoff Guided Early Stopping and Checkpoint Averaging.	CoRR	2023	DBLP DOI BibTeX RDF
17	Gautam Kamath 0001, Argyris Mouzakis, Matthew Regehr, Vikrant Singhal, Thomas Steinke 0002, Jonathan R. Ullman	A Bias-Variance-Privacy Trilemma for Statistical Estimation.	CoRR	2023	DBLP DOI BibTeX RDF
17	Divin Yan, Gengchen Wei, Chen Yang, Shengzhong Zhang, Zengfeng Huang	Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition.	CoRR	2023	DBLP DOI BibTeX RDF
17	Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli	Interpretable Linear Dimensionality Reduction based on Bias-Variance Analysis.	CoRR	2023	DBLP DOI BibTeX RDF
17	Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro	Multi-Task Bias-Variance Trade-Off Through Functional Constraints.	ICASSP	2023	DBLP DOI BibTeX RDF
17	Jonas Lindenberger, Stefan Schuster, Oliver Lang, Alexander Haberl, Clemens Staudinger, Theresa Roland, Mario Huemer	Bias, Variance, and Threshold Level of the Least Squares Pitch Estimator with Windowed Data.	ACSSC	2023	DBLP DOI BibTeX RDF
17	Ruoxuan Xiong, Alex Chin, Sean Taylor	Bias-Variance Tradeoffs for Designing Simultaneous Temporal Experiments.	CDPD	2023	DBLP BibTeX RDF
17	Divin Yan, Gengchen Wei, Chen Yang, Shengzhong Zhang, Zengfeng Huang	Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition.	NeurIPS	2023	DBLP BibTeX RDF
17	Sebastian Gruber 0001, Florian Buettner 0001	Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition.	AISTATS	2023	DBLP BibTeX RDF
17	Fangyuan Wang, Ming Hao, Yuhai Shi, Bo Xu	Lead ASR Models to Generalize Better Using Approximated Bias-Variance Tradeoff.	ICONIP (7)	2023	DBLP DOI BibTeX RDF
17	Neha Gupta, Jamie Smith, Ben Adlam, Zelda E. Mariet	Ensembles of Classifiers: a Bias-Variance Perspective.	Trans. Mach. Learn. Res.	2022	DBLP BibTeX RDF
17	Guocheng Liao, Yu Su 0013, Juba Ziani, Adam Wierman, Jianwei Huang 0001	The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition.	SIGMETRICS Perform. Evaluation Rev.	2022	DBLP DOI BibTeX RDF
17	Peng Zhang 0002, Hui Gao, Zeting Hu, Meng Yang, Dawei Song 0001, Jun Wang 0012, Yuexian Hou, Bin Hu 0001	A bias-variance evaluation framework for information retrieval systems.	Inf. Process. Manag.	2022	DBLP DOI BibTeX RDF
17	Tomoya Murata, Taiji Suzuki	Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning.	CoRR	2022	DBLP BibTeX RDF
17	Bruno Loureiro, Cédric Gerbelot, Maria Refinetti, Gabriele Sicuro, Florent Krzakala	Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension.	CoRR	2022	DBLP BibTeX RDF
17	Danny Wood, Tingting Mu, Gavin Brown 0001	Bias-Variance Decompositions for Margin Losses.	CoRR	2022	DBLP DOI BibTeX RDF
17	Max Winkelmann, Constantin Vasconi, Steffen Müller 0002	Transfer Importance Sampling - How Testing Automated Vehicles in Multiple Test Setups Helps With the Bias-Variance Tradeoff.	CoRR	2022	DBLP DOI BibTeX RDF
17	Risto Vuorio, Jacob Beck, Shimon Whiteson, Jakob N. Foerster, Gregory Farquhar	An Investigation of the Bias-Variance Tradeoff in Meta-Gradients.	CoRR	2022	DBLP DOI BibTeX RDF
17	Sebastian G. Gruber, Florian Buettner 0001	Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition.	CoRR	2022	DBLP DOI BibTeX RDF
17	Neha Gupta, Jamie Smith, Ben Adlam, Zelda Mariet	Ensembling over Classifiers: a Bias-Variance Perspective.	CoRR	2022	DBLP DOI BibTeX RDF
17	Jason W. Rocks, Pankaj Mehta	Bias-variance decomposition of overparameterized regression with random linear features.	CoRR	2022	DBLP DOI BibTeX RDF
17	Juan Cerviño, Juan Andrés Bazerque, Miguel Calvo-Fullana, Alejandro Ribeiro	Multi-task Bias-Variance Trade-off Through Functional Constraints.	CoRR	2022	DBLP DOI BibTeX RDF
17	Stefano Vigogna, Giacomo Meanti, Ernesto De Vito, Lorenzo Rosasco	Multiclass learning with margin: exponential rates with no bias-variance trade-off.	CoRR	2022	DBLP BibTeX RDF
17	Ben Adlam, Neha Gupta, Zelda Mariet, Jamie Smith	Understanding the bias-variance tradeoff of Bregman divergences.	CoRR	2022	DBLP BibTeX RDF
17	Claudia V. Roberts, Ehtsham Elahi, Ashok Chandrashekar	On the Bias-Variance Characteristics of LIME and SHAP in High Sparsity Movie Recommendation Explanation Tasks.	CoRR	2022	DBLP DOI BibTeX RDF
17	Shinho Lee, Wookhyun Jung, Wonrak Lee, Hyung-Geun Oh, Eui Tak Kim	Android malware dataset construction methodology to minimize bias-variance tradeoff.	ICT Express	2022	DBLP DOI BibTeX RDF
17	Tahra L. Eissa, Joshua I. Gold, Kresimir Josic, Zachary P. Kilpatrick	Suboptimal human inference can invert the bias-variance trade-off for decisions with asymmetric evidence.	PLoS Comput. Biol.	2022	DBLP DOI BibTeX RDF
17	Yao Zhou, Jun Wu 0019, Haixun Wang, Jingrui He	Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning.	CIKM	2022	DBLP DOI BibTeX RDF
17	Yiding Feng, Ronen Gradwohl, Jason D. Hartline, Aleck C. Johnsen, Denis Nekipelov	Bias-Variance Games.	EC	2022	DBLP DOI BibTeX RDF
17	Tomoya Murata, Taiji Suzuki	Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning.	NeurIPS	2022	DBLP BibTeX RDF
17	Max Winkelmann, Constantin Vasconi, Steffen Müller 0002	Transfer Importance Sampling - How Testing Automated Vehicles in Multiple Test Setups Helps With the Bias-Variance Tradeoff.	ITSC	2022	DBLP DOI BibTeX RDF
17	Stefano Vigogna, Giacomo Meanti, Ernesto De Vito, Lorenzo Rosasco	Multiclass learning with margin: exponential rates with no bias-variance trade-off.	ICML	2022	DBLP BibTeX RDF
17	Bruno Loureiro, Cédric Gerbelot, Maria Refinetti, Gabriele Sicuro, Florent Krzakala	Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension.	ICML	2022	DBLP BibTeX RDF
17	Anna Korba, François Portier	Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff.	AISTATS	2022	DBLP BibTeX RDF
17	Danny Wood, Tingting Mu, Gavin Brown 0001	Bias-Variance Decompositions for Margin Losses.	AISTATS	2022	DBLP BibTeX RDF
17	Licong Lin, Edgar Dobriban	What Causes the Test Error? Going Beyond Bias-Variance via ANOVA.	J. Mach. Learn. Res.	2021	DBLP BibTeX RDF
17	Takumi Aotani, Taisuke Kobayashi, Kenji Sugimoto	Meta-Optimization of Bias-Variance Trade-Off in Stochastic Model Learning.	IEEE Access	2021	DBLP DOI BibTeX RDF
17	Thiago Salles, Leonardo Rocha 0001, Marcos André Gonçalves	A bias-variance analysis of state-of-the-art random forest text classifiers.	Adv. Data Anal. Classif.	2021	DBLP DOI BibTeX RDF
17	Ting-Han Fan, Peter J. Ramadge	Explaining Off-Policy Actor-Critic From A Bias-Variance Perspective.	CoRR	2021	DBLP BibTeX RDF
17	Helong Zhou, Liangchen Song, Jiajie Chen, Ye Zhou, Guoli Wang, Junsong Yuan, Qian Zhang 0009	Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective.	CoRR	2021	DBLP BibTeX RDF
17	Tomoya Murata, Taiji Suzuki	Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning.	CoRR	2021	DBLP BibTeX RDF
17	Yehuda Dar, Vidya Muthukumar, Richard G. Baraniuk	A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning.	CoRR	2021	DBLP BibTeX RDF
17	Guocheng Liao, Yu Su 0013, Juba Ziani, Adam Wierman, Jianwei Huang 0001	The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition.	CoRR	2021	DBLP BibTeX RDF
17	Yaodong Yu, Zitong Yang, Edgar Dobriban, Jacob Steinhardt, Yi Ma 0001	Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition.	CoRR	2021	DBLP BibTeX RDF
17	Alexander Shekhovtsov	Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators.	CoRR	2021	DBLP BibTeX RDF
17		A Mathematical Foundation for Robust Machine Learning based on Bias-Variance Trade-off.	CoRR	2021	DBLP BibTeX RDF
17	Jing Gao	Bias-variance decomposition of absolute errors for diagnosing regression models of continuous data.	Patterns	2021	DBLP DOI BibTeX RDF
17	Xinjie Lan, Bin Zhu, Charles Boncelet, Kenneth E. Barner	Beyond the Bias Variance Trade-Off: A Mutual Information Trade-Off in Deep Learning.	MLSP	2021	DBLP DOI BibTeX RDF
17	Guocheng Liao, Yu Su 0013, Juba Ziani, Adam Wierman, Jianwei Huang 0001	The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition.	EC	2021	DBLP DOI BibTeX RDF
17	Alexander Shekhovtsov	Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators.	GCPR	2021	DBLP DOI BibTeX RDF
17	Yifan Hu, Xin Chen, Niao He	On the Bias-Variance-Cost Tradeoff of Stochastic Optimization.	NeurIPS	2021	DBLP BibTeX RDF