Search results for "High-dimensions"

Hits ?▲	Authors	Title	Venue	Year	Link	Author keywords
35	Cheng Yang, Usama M. Fayyad, Paul S. Bradley	Efficient discovery of error-tolerant frequent itemsets in high dimensions.	KDD	2001	DBLP DOI BibTeX RDF	Error-tolerant frequent itemset, query selectivity estimation, clustering, collaborative filtering, high dimensions
30	Orlando A. Carvajal, Frederick W. Chapman, Keith O. Geddes	Hybrid symbolic-numeric integration in multiple dimensions via tensor-product series.	ISSAC	2005	DBLP DOI BibTeX RDF	Geddes series scheme, Geddes-Newton series expansions, approximation of functions, bilinear series, deconstruction/approximation/reconstruction technique (DART), multiple integration, splitting operator, tensor products, symbolic-numeric algorithms
29	Qingquan Wang, Lili Rong, Kai Yu	Towards a Categorical Matching Method to Process High-Dimensional Emergency Knowledge Structures.	ISNN (2)	2008	DBLP DOI BibTeX RDF	Matching Method, Categorical Knowledge Structure, Category Theory, semantic information, High-dimensions
28	Yoshihiko Hamamoto, Shunji Uchimura, Shingo Tomita	A Bootstrap Technique for Nearest Neighbor Classifier Design.	IEEE Trans. Pattern Anal. Mach. Intell.	1997	DBLP DOI BibTeX RDF	peaking phenomenon, small training sample size, Bootstrap, outlier, error rate, nearest neighbor classifier, high dimensions
26	Roland Nilsson, José M. Peña 0001, Johan Björkegren, Jesper Tegnér	Evaluating Feature Selection for SVMs in High Dimensions.	ECML	2006	DBLP DOI BibTeX RDF
25	Sébastien Piccand, Michael O'Neill 0001, Jacqueline Walker	Scalability of particle swarm algorithms.	GECCO	2007	DBLP DOI BibTeX RDF	optimization, swarm intelligence, high dimensionality
23	Charu C. Aggarwal	On the use of Human-Computer Interaction for Projected Nearest Neighbor Search.	Data Min. Knowl. Discov.	2006	DBLP DOI BibTeX RDF	nearest neighbor search, projected clustering, high dimensions
23	Charu C. Aggarwal, Philip S. Yu	Redefining Clustering for High-Dimensional Applications.	IEEE Trans. Knowl. Data Eng.	2002	DBLP DOI BibTeX RDF	data mining, clustering, high dimensions, dimensionality curse
23	Gonzalo Navarro 0001, Nora Reyes	Dynamic Spatial Approximation Trees.	SCCC	2001	DBLP DOI BibTeX RDF	metric spaces, high dimensions, proximity searching
23	Ali Saman Tosun	Threshold Based Declustering in High Dimensions.	DEXA	2005	DBLP DOI BibTeX RDF
22	Piyush Kumar, Joseph S. B. Mitchell, E. Alper Yildirim	Approximate minimum enclosing balls in high dimensions using core-sets.	ACM J. Exp. Algorithmics	2003	DBLP DOI BibTeX RDF	minimum enclosing ball, approximation algorithms, second-order cone programming
21	Cédric Gerbelot	Statistical learning in high dimensions: a rigorous statistical physics approach. (Apprentissage statistique en grandes dimensions: une approche rigoureuse par la physique statistique).		2022	RDF
19	Sameer A. Nene, Shree K. Nayar	Closest Point Search in High Dimensions.	CVPR	1996	DBLP DOI BibTeX RDF	projection search, searching by slicing, object recognition, benchmarks, Pattern classification, nearest neighbor, closest point
17	Alexandr Andoni, Piotr Indyk, Robert Krauthgamer, Huy L. Nguyen	Approximate line nearest neighbor in high dimensions.	SODA	2009	DBLP DOI BibTeX RDF
17	Sariel Har-Peled, Kasturi R. Varadarajan	Projective clustering in high dimensions using core-sets.	SCG	2002	DBLP DOI BibTeX RDF	computational convexity, projective clustering
15	Liliana Forzani, Antonella Gieco, Carlos F. Tolmasky	Likelihood ratio test for partial sphericity in high and ultra-high dimensions.	J. Multivar. Anal.	2017	DBLP DOI BibTeX RDF
15	Fernando Cardoso, Claudio Cuevas, Georgi Vodev	High frequency dispersive estimates for the Schrödinger equation in high dimensions.	Asymptot. Anal.	2011	DBLP DOI BibTeX RDF
14	Flip Korn, Bernd-Uwe Pagel, Christos Faloutsos	On the 'Dimensionality Curse' and the 'Self-Similarity Blessing'.	IEEE Trans. Knowl. Data Eng.	2001	DBLP DOI BibTeX RDF	fractals, Nearest-neighbor search, multimedia indexing
14	Heng Tao Shen, Xiaofang Zhou 0001, Aoying Zhou	An adaptive and dynamic dimensionality reduction method for high-dimensional indexing.	VLDB J.	2007	DBLP DOI BibTeX RDF	Dimensionality reduction, Projection, Subspace, High-dimensional indexing, Correlated clustering
14	Zhenjie Zhang, Xinyu Guo, Hua Lu 0001, Anthony K. H. Tung, Nan Wang	Discovering strong skyline points in high dimensional spaces.	CIKM	2005	DBLP DOI BibTeX RDF	skyline, high dimensional space
14	Hui Jin, Beng Chin Ooi, Heng Tao Shen, Cui Yu, Aoying Zhou	An Adaptive and Efficient Dimensionality Reduction Algorithm for High-Dimensional Indexing.	ICDE	2003	DBLP DOI BibTeX RDF
14	Bernd-Uwe Pagel, Flip Korn, Christos Faloutsos	Deflating the Dimensionality Curse Using Multiple Fractal Dimensions.	ICDE	2000	DBLP DOI BibTeX RDF
13	Ekasit Kijsipongse, Sudsanguan Ngamsuriyaroj	Column-Based Partitioning for Data in High Dimensional Space.	ICPP	2007	DBLP DOI BibTeX RDF
13	Frédéric Chazal, Steve Oudot	Towards persistence-based reconstruction in euclidean spaces.	SCG	2008	DBLP DOI BibTeX RDF	cech complex, manifold reconstruction, rips complex, filtration, persistent homology, witness complex
12	Alexandru C. Telea, Alister Machado, Yu Wang	Seeing is Learning in High Dimensions: The Synergy Between Dimensionality Reduction and Machine Learning.	SN Comput. Sci.	2024	DBLP DOI BibTeX RDF
12	Clara Guilhaumon, Nicolas Hascoët, Francisco Chinesta, Marc Lavarde, Fatima Daim	Data Augmentation for Regression Machine Learning Problems in High Dimensions.	Comput.	2024	DBLP DOI BibTeX RDF
12	Yun-Feng Lo, Yen-Chi Lee, Min-Hsiu Hsieh	Degradability of Modified Landau-Streater Type Low-Noise Quantum Channels in High Dimensions.	CoRR	2024	DBLP DOI BibTeX RDF
12	Johannes Hertrich	Fast Kernel Summation in High Dimensions via Slicing and Fourier Transforms.	CoRR	2024	DBLP DOI BibTeX RDF
12	Zhizhang Wu, Renaud Raquépas, Jack Xin, Zhiwen Zhang	Computing large deviation rate functions of entropy production for diffusion processes in the vanishing-noise limit and high dimensions by an interacting particle method.	CoRR	2024	DBLP DOI BibTeX RDF
12	Yuan Chen, Dongbin Xiu, Xiangxiong Zhang	On enforcing non-negativity in polynomial approximations in high dimensions.	CoRR	2024	DBLP DOI BibTeX RDF
12	Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi	Vanilla Bayesian Optimization Performs Great in High Dimensions.	CoRR	2024	DBLP DOI BibTeX RDF
12	Stefan Sylvius Wagner, Stefan Harmeling	Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations.	CoRR	2024	DBLP DOI BibTeX RDF
12	Yutaro Chiyo, Kazuma Sugawara, Tomomi Yokota	Boundedness criteria for a class of indirect (and direct) chemotaxis-consumption models with signal-dependent sensitivity in high dimensions.	Appl. Math. Lett.	2024	DBLP DOI BibTeX RDF
12	Santhosh Karnik, Rongrong Wang, Mark A. Iwen	Neural network approximation of continuous functions in high dimensions with applications to inverse problems.	J. Comput. Appl. Math.	2024	DBLP DOI BibTeX RDF
12	Taehoon Ahn 0001, Chaeyoon Chung, Hee-Kap Ahn, Sang Won Bae, Otfried Cheong, Sang Duk Yoon	Minimum-Width Double-Slabs and Widest Empty Slabs in High Dimensions.	LATIN (1)	2024	DBLP DOI BibTeX RDF
12	Simon Martin, Francis Bach, Giulio Biroli	On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions.	AISTATS	2024	DBLP BibTeX RDF
12	Golara Ahmadi Azar, Melika Emami, Alyson K. Fletcher, Sundeep Rangan	Learning Embedding Representations in High Dimensions.	CISS	2024	DBLP DOI BibTeX RDF
12	Liang-Sian Lin, Yao-San Lin, Der-Chiang Li, Yun-Hsuan Liu	Improved learning performance for small datasets in high dimensions by new dual-net model for non-linear interpolation virtual sample generation.	Decis. Support Syst.	2023	DBLP DOI BibTeX RDF
12	Paul Harrison	langevitour: Smooth Interactive Touring of High Dimensions, Demonstrated with scRNA-Seq Data.	R J.	2023	DBLP DOI BibTeX RDF
12	Fatma Sevinç Kurnaz, Peter Filzmoser	Robust and sparse multinomial regression in high dimensions.	Data Min. Knowl. Discov.	2023	DBLP DOI BibTeX RDF
12	Yoshihito Kazashi, Fabio Nobile	Density Estimation in RKHS with Application to Korobov Spaces in High Dimensions.	SIAM J. Numer. Anal.	2023	DBLP DOI BibTeX RDF
12	Jose Laborde, Paul A. Stewart, Zhihua Chen, Yian A. Chen, Naomi C. Brownstein	Sparse clusterability: testing for cluster structure in high dimensions.	BMC Bioinform.	2023	DBLP DOI BibTeX RDF
12	Shanyin Tong, Georg Stadler	Large Deviation Theory-based Adaptive Importance Sampling for Rare Events in High Dimensions.	SIAM/ASA J. Uncertain. Quantification	2023	DBLP DOI BibTeX RDF
12	Kai Lagemann, Christian Lagemann, Bernd Taschler, Sach Mukherjee	Deep learning of causal structures in high dimensions under data limitations.	Nat. Mac. Intell.	2023	DBLP DOI BibTeX RDF
12	Aditya Deshmukh, Jing Liu, Venugopal V. Veeravalli	Robust Mean Estimation in High Dimensions: An Outlier-Fraction Agnostic and Efficient Algorithm.	IEEE Trans. Inf. Theory	2023	DBLP DOI BibTeX RDF
12	Wei Cai	DeepMartNet - A Martingale based Deep Neural Network learning algorithm for Eigenvalue Problems in High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Julia Rozanova, Marco Valentino, Lucas C. Cordeiro, André Freitas	Interventional Probing in High Dimensions: An NLI Case Study.	CoRR	2023	DBLP DOI BibTeX RDF
12	Patrick Cheridito, Florian Rossmannek	Efficient Sobolev approximation of linear parabolic PDEs in high dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Marco Cuturi, Michal Klein, Pierre Ablin	Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps.	CoRR	2023	DBLP DOI BibTeX RDF
12	Hadley Black, Eric Blais, Nathaniel Harms	Testing Convexity of Discrete Sets in High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Sarthak Choudhary, Aashish Kolluri, Prateek Saxena	Attacking Byzantine Robust Aggregation in High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Ansgar Steland	On Extreme Value Asymptotics of Projected Sample Covariances in High Dimensions with Applications in Finance and Convolutional Networks.	CoRR	2023	DBLP DOI BibTeX RDF
12	Golara Ahmadi Azar, Melika Emami, Alyson K. Fletcher, Sundeep Rangan	Estimation of embedding vectors in high dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Kartheek Bondugula, Santiago Mazuelas, Aritz Pérez	Efficient Learning of Minimax Risk Classifiers in High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Jonathan Schmidt, Philipp Hennig, Jörg Nick, Filip Tronarp	The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Kerun Xu, Miranda C. Holmes-Cerfon	Monte Carlo on manifolds in high dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Vesa Kaarnioja, Frances Y. Kuo, Ian H. Sloan	Lattice-based kernel approximation and serendipitous weights for parametric PDEs in very high dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Mahyar Khayatkhoei, Wael AbdAlmageed	Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Nishil Patel, Sebastian Lee, Stefano Sarao Mannelli, Sebastian Goldt, Adrew Saxe	The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Kuo-Wei Lai, Vidya Muthukumar	General Loss Functions Lead to (Approximate) Interpolation in High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Urte Adomaityte, Gabriele Sicuro, Pierpaolo Vivo	Classification of Superstatistical Features in High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani	Demystifying Disagreement-on-the-Line in High Dimensions.	CoRR	2023	DBLP DOI BibTeX RDF
12	Kasper Overgaard Mortensen, Fatemeh Zardbani, Mohammad Ahsanul Haque, Steinn Ymir Agustsson, Davide Mottin, Philip Hofmann, Panagiotis Karras	Marigold: Efficient k-means Clustering in High Dimensions. (PDF / PS)	Proc. VLDB Endow.	2023	DBLP DOI BibTeX RDF
12	Bihao Su, Chenglong Xu, Changtao Sheng	A new 'walk on spheres' type method for fractional diffusion equation in high dimensions based on the Feynman-Kac formulas.	Appl. Math. Lett.	2023	DBLP DOI BibTeX RDF
12	Brittany Green, Heng Lian, Yan Yu, Tianhai Zu	Semiparametric penalized quadratic inference functions for longitudinal data in ultra-high dimensions.	J. Multivar. Anal.	2023	DBLP DOI BibTeX RDF
12	Masashi Hyodo, Takahiro Nishiyama, Tatjana Pavlenko	A Behrens-Fisher problem for general factor models in high dimensions.	J. Multivar. Anal.	2023	DBLP DOI BibTeX RDF
12	Nina Dörnemann	Likelihood ratio tests under model misspecification in high dimensions.	J. Multivar. Anal.	2023	DBLP DOI BibTeX RDF
12	Philippe Boileau, Nima S. Hejazi, Mark J. van der Laan, Sandrine Dudoit	Cross-Validated Loss-based Covariance Matrix Estimator Selection in High Dimensions.	J. Comput. Graph. Stat.	2023	DBLP DOI BibTeX RDF
12	Robert Beinert	Approximation of curve-based sleeve functions in high dimensions.	Adv. Comput. Math.	2023	DBLP DOI BibTeX RDF
12	Haotian Zhang, Xiaoguang Ma, Zhizhe Lin	SAE-SV: A Stacked-AutoEncoder and Soft Voting Joint Approach Based on Small Dataset with High Dimensions for Inhibitory Potency Prediction.	ISAIMS	2023	DBLP DOI BibTeX RDF
12	Jian Tan, Niv Nayman	Two-stage Kernel Bayesian Optimization in High Dimensions.	UAI	2023	DBLP BibTeX RDF
12	Kartheek Bondugula, Santiago Mazuelas, Aritz Pérez	Efficient Learning of Minimax Risk Classifiers in High Dimensions.	UAI	2023	DBLP BibTeX RDF
12	Fan Zhou, Ping Li 0001, Cun-Hui Zhang	Universal Bias Reduction in Estimation of Smooth Additive Function in High Dimensions.	ALT	2023	DBLP BibTeX RDF
12	Marija Iloska, Mónica F. Bugallo	Generalized Two-Stage Particle Filter for High Dimensions.	ICASSP	2023	DBLP DOI BibTeX RDF
12	Ioannis Psarros, Dennis Rohde	Random Projections for Curves in High Dimensions.	SoCG	2023	DBLP DOI BibTeX RDF
12	Mike Van Ness, Tomas M. Bosschieter, Roberto Halpin-Gregorio, Madeleine Udell	The Missing Indicator Method: From Low to High Dimensions.	KDD	2023	DBLP DOI BibTeX RDF
12	Julia Rozanova, Marco Valentino, Lucas C. Cordeiro, André Freitas	Interventional Probing in High Dimensions: An NLI Case Study.	EACL (Findings)	2023	DBLP DOI BibTeX RDF
12	Tao Zhang, Yaowu Zhang, Tingyou Zhou	Statistical Insights into HSIC in High Dimensions.	NeurIPS	2023	DBLP BibTeX RDF
12	Kai Tan, Pierre C. Bellec	Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions.	NeurIPS	2023	DBLP BibTeX RDF
12	Alexandr Andoni, Piotr Indyk, Sepideh Mahabadi, Shyam Narayanan	Differentially Private Approximate Near Neighbor Counting in High Dimensions.	NeurIPS	2023	DBLP BibTeX RDF
12	Jonathan Schmidt, Philipp Hennig, Jörg Nick, Filip Tronarp	The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions.	NeurIPS	2023	DBLP BibTeX RDF
12	Urte Adomaityte, Gabriele Sicuro, Pierpaolo Vivo	Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach.	NeurIPS	2023	DBLP BibTeX RDF
12	Wanshan Li, Daren Wang, Alessandro Rinaldo	Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions.	ICML	2023	DBLP BibTeX RDF
12	Alexandru Tifrea, Jacob Clarysse, Fanny Yang	Margin-based sampling in high dimensions: When being active is less efficient than staying passive.	ICML	2023	DBLP BibTeX RDF
12	Mahyar Khayatkhoei, Wael Abd-Almageed	Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High Dimensions.	ICML	2023	DBLP BibTeX RDF
12	Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani	Demystifying Disagreement-on-the-Line in High Dimensions.	ICML	2023	DBLP BibTeX RDF
12	Marco Cuturi, Michal Klein, Pierre Ablin	Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps.	ICML	2023	DBLP BibTeX RDF
12	Edgar Chávez, Eric Sadit Tellez	Turbo Scan: Fast Sequential Nearest Neighbor Search in High Dimensions.	SISAP	2023	DBLP DOI BibTeX RDF
12	Subha Maity, Yuekai Sun, Moulinath Banerjee	Meta-analysis of heterogeneous data: integrative sparse regression in high-dimensions.	J. Mach. Learn. Res.	2022	DBLP BibTeX RDF
12	Rafael Izbicki, Gilson Y. Shimizu, Rafael Bassi Stern	CD-split and HPD-split: Efficient Conformal Regions in High Dimensions.	J. Mach. Learn. Res.	2022	DBLP BibTeX RDF
12	Shaogao Lv, Heng Lian	Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions.	J. Mach. Learn. Res.	2022	DBLP BibTeX RDF
12	Srijata Samanta, Kshitij Khare, George Michailidis	A generalized likelihood-based Bayesian approach for scalable joint regression and covariance selection in high dimensions.	Stat. Comput.	2022	DBLP DOI BibTeX RDF
12	Jing Li, Kuijie Li	The Defocusing Energy-Supercritical Nonlinear Schrödinger Equation in High Dimensions.	SIAM J. Math. Anal.	2022	DBLP DOI BibTeX RDF
12	Sharif Rahman, Ramin Jahanbin	A Spline Dimensional Decomposition for Uncertainty Quantification in High Dimensions.	SIAM/ASA J. Uncertain. Quantification	2022	DBLP DOI BibTeX RDF
12	Hua Wang, Yachong Yang, Weijie J. Su	The Price of Competition: Effect Size Heterogeneity Matters in High Dimensions.	IEEE Trans. Inf. Theory	2022	DBLP DOI BibTeX RDF
12	Ben Adcock, Juan M. Cardenas, Nick C. Dexter, Sebastian Moraga	Towards optimal sampling for learning sparse approximation in high dimensions.	CoRR	2022	DBLP BibTeX RDF
12	Paul M. Baggenstoss	Using the Projected Belief Network at High Dimensions.	CoRR	2022	DBLP DOI BibTeX RDF
12	Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta	When Does Differentially Private Learning Not Suffer in High Dimensions?	CoRR	2022	DBLP DOI BibTeX RDF
12	Mike Van Ness, Tomas M. Bosschieter, Roberto Halpin-Gregorio, Madeleine Udell	The Missing Indicator Method: From Low to High Dimensions.	CoRR	2022	DBLP DOI BibTeX RDF
12	Niladri Das, Jed A. Duersch, Thomas A. Catanach	Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions.	CoRR	2022	DBLP DOI BibTeX RDF