Brijnesh J. Jain

96 papers A* 1A 4B 13C 3Misc 5Journal 53Unranked 17

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	An average-compress algorithm for the sample mean problem under dynamic time warping. J. Glob. Optim. Brijnesh J. Jain, Vincent Froese, David Schultz
2023	J	`jnl`	Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series. Algorithmica Vincent Froese, Brijnesh J. Jain, Maciej Rymar, Mathias Weller
2023	J	`jnl`	When algorithm selection meets Bi-linear Learning to Rank: accuracy and inference time trade off with candidates expansion. Int. J. Data Sci. Anal. Jing Yuan, Christian Geißler, Weijia Shao, Andreas Lommatzsch, Brijnesh J. Jain
2021	J	`jnl`	Warped softmax regression for time series classification. Knowl. Inf. Syst. Brijnesh J. Jain
2020	J	`jnl`	Comparing temporal graphs using dynamic time warping. Soc. Netw. Anal. Min. Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, Malte Renken
2020	J	`jnl`	Sufficient conditions for the existence of a sample mean of time series under dynamic time warping. Ann. Math. Artif. Intell. Brijnesh J. Jain, David Schultz
2019	J	`jnl`	An Average-Compress Algorithm for the Sample Mean Problem under Dynamic Time Warping. CoRR Brijnesh J. Jain, Vincent Froese, David Schultz
2019	—	`conf`	Comparing Temporal Graphs Using Dynamic Time Warping. COMPLEX NETWORKS (2) Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, Malte Renken
2019	J	`jnl`	Exact mean computation in dynamic time warping spaces. Data Min. Knowl. Discov. Markus Brill, Till Fluschnik, Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, David Schultz
2019	J	`jnl`	Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series. CoRR Vincent Froese, Brijnesh J. Jain, Maciej Rymar, Mathias Weller
2019	J	`jnl`	Making the Dynamic Time Warping Distance Warping-Invariant. CoRR Brijnesh J. Jain
2019	J	`jnl`	Making the dynamic time warping distance warping-invariant. Pattern Recognit. Brijnesh J. Jain
2019	J	`jnl`	Revisiting inaccuracies of time series averaging under dynamic time warping. Pattern Recognit. Lett. Brijnesh J. Jain
2018	J	`jnl`	Asymmetric learning vector quantization for efficient nearest neighbor classification in dynamic time warping spaces. Pattern Recognit. Brijnesh J. Jain, David Schultz
2018	J	`jnl`	Comparing Temporal Graphs Using Dynamic Time Warping. CoRR Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, Malte Renken
2018	Misc	`conf`	Condorcet's Jury Theorem for Consensus Clustering. KI Brijnesh J. Jain
2018	A	`conf`	Exact Mean Computation in Dynamic Time Warping Spaces. SDM Markus Brill, Till Fluschnik, Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, David Schultz
2018	—	`conf`	Gamification in E-Commerce: Tangible vs. Intangible Rewards. MindTrek Michael Meder, Till Plumbaum, Aleksander Raczkowski, Brijnesh J. Jain, Sahin Albayrak
2018	J	`jnl`	Nonsmooth analysis and subgradient methods for averaging in dynamic time warping spaces. Pattern Recognit. David Schultz, Brijnesh J. Jain
2018	J	`jnl`	Revisiting Inaccuracies of Time Series Averaging under Dynamic Time Warping. CoRR Brijnesh J. Jain
2018	J	`jnl`	Semi-Metrification of the Dynamic Time Warping Distance. CoRR Brijnesh J. Jain
2018	J	`jnl`	The Mean Partition Theorem in consensus clustering. Pattern Recognit. Brijnesh J. Jain
2017	J	`jnl`	Asymmetric Learning Vector Quantization for Efficient Nearest Neighbor Classification in Dynamic Time Warping Spaces. CoRR Brijnesh J. Jain, David Schultz
2017	J	`jnl`	Consistency of mean partitions in consensus clustering. Pattern Recognit. Brijnesh J. Jain
2017	J	`jnl`	Exact Mean Computation in Dynamic Time Warping Spaces. CoRR Markus Brill, Till Fluschnik, Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, David Schultz
2017	J	`jnl`	Nonsmooth Analysis and Subgradient Methods for Averaging in Dynamic Time Warping Spaces. CoRR David Schultz, Brijnesh J. Jain
2017	J	`jnl`	Optimal Warping Paths are unique for almost every pair of Time Series. CoRR Brijnesh J. Jain, David Schultz
2017	J	`jnl`	Warped-Linear Models for Time Series Classification. CoRR Brijnesh J. Jain
2016	J	`jnl`	A Reduction Theorem for the Sample Mean in Dynamic Time Warping Spaces. CoRR Brijnesh J. Jain, David Schultz
2016	J	`jnl`	Condorcet's Jury Theorem for Consensus Clustering. CoRR Brijnesh J. Jain
2016	J	`jnl`	Homogeneity of Cluster Ensembles. CoRR Brijnesh J. Jain
2016	J	`jnl`	On the geometry of graph spaces. Discret. Appl. Math. Brijnesh J. Jain
2016	J	`jnl`	Statistical graph space analysis. Pattern Recognit. Brijnesh J. Jain
2016	J	`jnl`	The Mean Partition Theorem of Consensus Clustering. CoRR Brijnesh J. Jain
2015	J	`jnl`	Asymptotic Behavior of Mean Partitions in Consensus Clustering. CoRR Brijnesh J. Jain
2015	—	`conf`	Dimension Reduction in Dissimilarity Spaces for Time Series Classification. AALTD@PKDD/ECML (Revised Selected Papers) Brijnesh J. Jain, Stephan Spiegel
2015	J	`jnl`	Generalized Gradient Learning on Time Series under Elastic Transformations. CoRR Brijnesh J. Jain
2015	J	`jnl`	Generalized gradient learning on time series. Mach. Learn. Brijnesh J. Jain
2015	J	`jnl`	Geometry of Graph Edit Distance Spaces. CoRR Brijnesh J. Jain
2015	J	`jnl`	Properties of the Sample Mean in Graph Spaces and the Majorize-Minimize-Mean Algorithm. CoRR Brijnesh J. Jain
2015	—	`conf`	Time Series Classification in Dissimilarity Spaces. AALTD@PKDD/ECML Brijnesh J. Jain, Stephan Spiegel
2014	—	`conf`	Flip-Flop Sublinear Models for Graphs. S+SSPR Brijnesh J. Jain
2014	J	`jnl`	Flip-Flop Sublinear Models for Graphs: Proof of Theorem 1. CoRR Brijnesh J. Jain
2014	B	`conf`	Margin Perceptrons for Graphs. ICPR Brijnesh J. Jain
2014	J	`jnl`	Sublinear Models for Graphs. CoRR Brijnesh J. Jain
2013	—	`conf`	A 3D approach to recommender system evaluation. CSCW Companion Alan Said, Brijnesh J. Jain, Sahin Albayrak
2013	—	`conf`	Mixtures of Radial Densities for Clustering Graphs. CAIP (1) Brijnesh J. Jain
2013	A	`conf`	User-centric evaluation of a K-furthest neighbor collaborative filtering recommender algorithm. CSCW Alan Said, Ben Fields, Brijnesh J. Jain, Sahin Albayrak
2012	Misc	`conf`	Analyzing weighting schemes in collaborative filtering: cold start, post cold start and power users. SAC Alan Said, Brijnesh J. Jain, Sahin Albayrak
2012	—	`conf`	Correlating perception-oriented aspects in user-centric recommender system evaluation. IIiX Alan Said, Brijnesh J. Jain, Andreas Lommatzsch, Sahin Albayrak
2012	A*	`conf`	Estimating the magic barrier of recommender systems: a user study. SIGIR Alan Said, Brijnesh J. Jain, Sascha Narr, Till Plumbaum, Sahin Albayrak, Christian Scheel
2012	A	`conf`	KMulE: a framework for user-based comparison of recommender algorithms. IUI Alan Said, Ernesto William De Luca, Benjamin Kille, Brijnesh J. Jain, Immo Micus, Sahin Albayrak
2012	J	`jnl`	Learning in Riemannian Orbifolds CoRR Brijnesh J. Jain, Klaus Obermayer
2012	J	`jnl`	Maximum likelihood method for parameter estimation of bell-shaped functions on graphs. Pattern Recognit. Lett. Brijnesh J. Jain
2012	A	`conf`	Users and Noise: The Magic Barrier of Recommender Systems. UMAP Alan Said, Brijnesh J. Jain, Sascha Narr, Till Plumbaum
2011	J	`jnl`	Extending Bron Kerbosch for Solving the Maximum Weight Clique Problem CoRR Brijnesh J. Jain, Klaus Obermayer
2011	—	`conf`	Generalized Learning Graph Quantization. GbRPR Brijnesh J. Jain, Klaus Obermayer
2011	J	`jnl`	Graph quantization. Comput. Vis. Image Underst. Brijnesh J. Jain, Klaus Obermayer
2011	—	`conf`	Maximum Likelihood for Gaussians on Graphs. GbRPR Brijnesh J. Jain, Klaus Obermayer
2010	J	`jnl`	A Maximum Common Subgraph Kernel Method for Predicting the Chromosome Aberration Test. J. Chem. Inf. Model. Johannes Mohr, Brijnesh J. Jain, Andreas Sutter, Antonius ter Laak, Thomas Steger-Hartmann, Nikolaus Heinrich, Klaus Obermayer
2010	J	`jnl`	Accelerating Competitive Learning Graph Quantization CoRR Brijnesh J. Jain, Klaus Obermayer
2010	B	`conf`	Consistent Estimator of Median and Mean Graph. ICPR Brijnesh J. Jain, Klaus Obermayer
2010	—	`conf`	Elkan's k-Means Algorithm for Graphs. MICAI (2) Brijnesh J. Jain, Klaus Obermayer
2010	J	`jnl`	Graph Quantization CoRR Brijnesh J. Jain, Klaus Obermayer
2010	—	`conf`	Large Sample Statistics in the Domain of Graphs. SSPR/SPR Brijnesh J. Jain, Klaus Obermayer
2010	—	`conf`	Learning Graph Quantization. SSPR/SPR Brijnesh J. Jain, S. Deepak Srinivasan, Alexander Tissen, Klaus Obermayer
2009	J	`jnl`	A Necessary and Sufficient Condition for Graph Matching Being Equivalent to the Maximum Weight Clique Problem CoRR Brijnesh J. Jain, Klaus Obermayer
2009	C	`conf`	Algorithms for the Sample Mean of Graphs. CAIP Brijnesh J. Jain, Klaus Obermayer
2009	B	`conf`	Bimal: Bipartite matching alignment for the contact map overlap problem. IJCNN Brijnesh J. Jain, Klaus Obermayer
2009	J	`jnl`	Elkan's k-Means for Graphs CoRR Brijnesh J. Jain, Klaus Obermayer
2009	B	`conf`	Multiple alignment of contact maps. IJCNN Brijnesh J. Jain, Brijnesh Stehr, Michael Lappe, Klaus Obermayer
2009	J	`jnl`	Structure Spaces. J. Mach. Learn. Res. Brijnesh J. Jain, Klaus Obermayer
2008	J	`jnl`	Molecule Kernels: A Descriptor- and Alignment-Free Quantitative Structure-Activity Relationship Approach. J. Chem. Inf. Model. Johannes Mohr, Brijnesh J. Jain, Klaus Obermayer
2008	B	`conf`	On the sample mean of graphs. IJCNN Brijnesh J. Jain, Klaus Obermayer
2007	—	`conf`	Joining Softassign and Dynamic Programming for the Contact Map Overlap Problem. BIRD Brijnesh J. Jain, Michael Lappe
2005	J	`jnl`	SVM learning with the Schur-Hadamard inner product for graphs. Neurocomputing Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki
2005	J	`jnl`	Solving inexact graph isomorphism problems using neural networks. Neurocomputing Brijnesh J. Jain, Fritz Wysotzki
2004	J	`jnl`	Central Clustering of Attributed Graphs. Mach. Learn. Brijnesh J. Jain, Fritz Wysotzki
2004	Misc	`conf`	Combining Recurrent Neural Networks and Support Vector Machines for Structural Pattern Recognition. KI Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki
2004	J	`jnl`	Discrimination networks for maximum selection. Neural Networks Brijnesh J. Jain, Fritz Wysotzki
2004	—	`conf`	Learning with Neural Networks in the Domain of Graphs. LWA Brijnesh J. Jain, Fritz Wysotzki
2004	B	`conf`	Multi-layer perceptron learning in the domain of attributed graphs. IJCNN Brijnesh J. Jain, Fritz Wysotzki
2004	B	`conf`	Neural methods for non-standard data. ESANN Barbara Hammer, Brijnesh J. Jain
2004	B	`conf`	SVM learning with the SH inner product. ESANN Peter Geibel, Brijnesh J. Jain, Fritz Wysotzki
2004	—	`conf`	Structural Perceptrons for Attributed Graphs. SSPR/SPR Brijnesh J. Jain, Fritz Wysotzki
2004	B	`conf`	The maximum weighted clique problem and Hopfield networks. ESANN Brijnesh J. Jain, Fritz Wysotzki
2003	—	`conf`	A Competitive Winner-Takes-All Architecture for Classification and Pattern Recognition of Structures. GbRPR Brijnesh J. Jain, Fritz Wysotzki
2003	B	`conf`	A Neural Graph Isomorphism Algorithm based on local Invariants. ESANN Brijnesh J. Jain, Fritz Wysotzki
2003	C	`conf`	A Novel Neural Network Approach to Solve Exact and Inexact Graph Isomorphism Problems. ICANN Brijnesh J. Jain, Fritz Wysotzki
2003	Misc	`conf`	A k-Winner-Takes-All Classifier for Structured Data. KI Brijnesh J. Jain, Fritz Wysotzki
2003	B	`conf`	An Associative Memory for the Automorphism Group of Structures. ESANN Brijnesh J. Jain, Fritz Wysotzki
2003	J	`jnl`	Automorphism Partitioning with Neural Networks. Neural Process. Lett. Brijnesh J. Jain, Fritz Wysotzki
2003	B	`conf`	Perceptron learning in the domain of graphs. IJCNN Brijnesh J. Jain, Fritz Wysotzki
2002	Misc	`conf`	Fast Winner-Takes-All Networks for the Maximum Clique Problem. KI Brijnesh J. Jain, Fritz Wysotzki
2001	C	`conf`	Efficient Pattern Discrimination with Inhibitory WTA Nets. ICANN Brijnesh J. Jain, Fritz Wysotzki
2001	B	`conf`	On the short-term-memory of WTA nets. ESANN Brijnesh J. Jain, Fritz Wysotzki