Brijnesh J. Jain

Publication Activity (10 Years)

Years Active: 2001-2023
Publications (10 Years): 34

Top Topics

Dynamic Time Warping

Top Venues

Pattern Recognit.

Publications

Vincent Froese, Brijnesh J. Jain, Maciej Rymar, Mathias Weller
Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series. Algorithmica 85 (2) (2023)
Jing Yuan, Christian Geißler, Weijia Shao, Andreas Lommatzsch, Brijnesh J. Jain
When algorithm selection meets Bi-linear Learning to Rank: accuracy and inference time trade off with candidates expansion. Int. J. Data Sci. Anal. 16 (2) (2023)
Brijnesh J. Jain, Vincent Froese, David Schultz
An average-compress algorithm for the sample mean problem under dynamic time warping. J. Glob. Optim. 86 (4) (2023)
Brijnesh J. Jain
Warped softmax regression for time series classification. Knowl. Inf. Syst. 63 (3) (2021)
Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, Malte Renken
Comparing temporal graphs using dynamic time warping. Soc. Netw. Anal. Min. 10 (1) (2020)
Brijnesh J. Jain, David Schultz
Sufficient conditions for the existence of a sample mean of time series under dynamic time warping. Ann. Math. Artif. Intell. 88 (4) (2020)
Vincent Froese, Brijnesh J. Jain, Maciej Rymar, Mathias Weller
Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series. CoRR (2019)
Brijnesh J. Jain
Making the Dynamic Time Warping Distance Warping-Invariant. CoRR (2019)
Markus Brill, Till Fluschnik, Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, David Schultz
Exact mean computation in dynamic time warping spaces. Data Min. Knowl. Discov. 33 (1) (2019)
Brijnesh J. Jain
Making the dynamic time warping distance warping-invariant. Pattern Recognit. 94 (2019)
Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, Malte Renken
Comparing Temporal Graphs Using Dynamic Time Warping. COMPLEX NETWORKS (2) (2019)
Brijnesh J. Jain
Revisiting inaccuracies of time series averaging under dynamic time warping. Pattern Recognit. Lett. 125 (2019)
Brijnesh J. Jain, Vincent Froese, David Schultz
An Average-Compress Algorithm for the Sample Mean Problem under Dynamic Time Warping. CoRR (2019)
Markus Brill, Till Fluschnik, Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, David Schultz
Exact Mean Computation in Dynamic Time Warping Spaces. SDM (2018)
Brijnesh J. Jain
Revisiting Inaccuracies of Time Series Averaging under Dynamic Time Warping. CoRR (2018)
Brijnesh J. Jain
Condorcet's Jury Theorem for Consensus Clustering. KI (2018)
Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, Malte Renken
Comparing Temporal Graphs Using Dynamic Time Warping. CoRR (2018)
Brijnesh J. Jain
Semi-Metrification of the Dynamic Time Warping Distance. CoRR (2018)
Brijnesh J. Jain, David Schultz
Asymmetric learning vector quantization for efficient nearest neighbor classification in dynamic time warping spaces. Pattern Recognit. 76 (2018)
Michael Meder, Till Plumbaum, Aleksander Raczkowski, Brijnesh J. Jain, Sahin Albayrak
Gamification in E-Commerce: Tangible vs. Intangible Rewards. MindTrek (2018)
David Schultz, Brijnesh J. Jain
Nonsmooth analysis and subgradient methods for averaging in dynamic time warping spaces. Pattern Recognit. 74 (2018)
Brijnesh J. Jain
The Mean Partition Theorem in consensus clustering. Pattern Recognit. 79 (2018)
David Schultz, Brijnesh J. Jain
Nonsmooth Analysis and Subgradient Methods for Averaging in Dynamic Time Warping Spaces. CoRR (2017)
Brijnesh J. Jain
Consistency of mean partitions in consensus clustering. Pattern Recognit. 71 (2017)
Markus Brill, Till Fluschnik, Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, David Schultz
Exact Mean Computation in Dynamic Time Warping Spaces. CoRR (2017)
Brijnesh J. Jain
Warped-Linear Models for Time Series Classification. CoRR (2017)
Brijnesh J. Jain, David Schultz
Optimal Warping Paths are unique for almost every pair of Time Series. CoRR (2017)
Brijnesh J. Jain, David Schultz
Asymmetric Learning Vector Quantization for Efficient Nearest Neighbor Classification in Dynamic Time Warping Spaces. CoRR (2017)
Brijnesh J. Jain
Condorcet's Jury Theorem for Consensus Clustering. CoRR (2016)
Brijnesh J. Jain
The Mean Partition Theorem of Consensus Clustering. CoRR (2016)
Brijnesh J. Jain, David Schultz
A Reduction Theorem for the Sample Mean in Dynamic Time Warping Spaces. CoRR (2016)
Brijnesh J. Jain
Statistical graph space analysis. Pattern Recognit. 60 (2016)
Brijnesh J. Jain
Homogeneity of Cluster Ensembles. CoRR (2016)
Brijnesh J. Jain
On the geometry of graph spaces. Discret. Appl. Math. 214 (2016)
Brijnesh J. Jain
Generalized gradient learning on time series. Mach. Learn. 100 (2-3) (2015)
Brijnesh J. Jain, Stephan Spiegel
Time Series Classification in Dissimilarity Spaces. AALTD@PKDD/ECML (2015)
Brijnesh J. Jain
Generalized Gradient Learning on Time Series under Elastic Transformations. CoRR (2015)
Brijnesh J. Jain
Properties of the Sample Mean in Graph Spaces and the Majorize-Minimize-Mean Algorithm. CoRR (2015)
Brijnesh J. Jain
Geometry of Graph Edit Distance Spaces. CoRR (2015)
Brijnesh J. Jain, Stephan Spiegel
Dimension Reduction in Dissimilarity Spaces for Time Series Classification. AALTD@PKDD/ECML (Revised Selected Papers) (2015)
Brijnesh J. Jain
Asymptotic Behavior of Mean Partitions in Consensus Clustering. CoRR (2015)
Brijnesh J. Jain
Flip-Flop Sublinear Models for Graphs: Proof of Theorem 1. CoRR (2014)
Brijnesh J. Jain
Sublinear Models for Graphs. CoRR (2014)
Brijnesh J. Jain
Margin Perceptrons for Graphs. ICPR (2014)
Brijnesh J. Jain
Flip-Flop Sublinear Models for Graphs. S+SSPR (2014)
Alan Said, Brijnesh J. Jain, Sahin Albayrak
A 3D approach to recommender system evaluation. CSCW Companion (2013)
Alan Said, Ben Fields, Brijnesh J. Jain, Sahin Albayrak
User-centric evaluation of a K-furthest neighbor collaborative filtering recommender algorithm. CSCW (2013)
Brijnesh J. Jain
Mixtures of Radial Densities for Clustering Graphs. CAIP (1) (2013)
Brijnesh J. Jain, Klaus Obermayer
Learning in Riemannian Orbifolds CoRR (2012)
Brijnesh J. Jain
Maximum likelihood method for parameter estimation of bell-shaped functions on graphs. Pattern Recognit. Lett. 33 (15) (2012)
Alan Said, Ernesto William De Luca, Benjamin Kille, Brijnesh J. Jain, Immo Micus, Sahin Albayrak
KMulE: a framework for user-based comparison of recommender algorithms. IUI (2012)
Alan Said, Brijnesh J. Jain, Sascha Narr, Till Plumbaum, Sahin Albayrak, Christian Scheel
Estimating the magic barrier of recommender systems: a user study. SIGIR (2012)
Alan Said, Brijnesh J. Jain, Sascha Narr, Till Plumbaum
Users and Noise: The Magic Barrier of Recommender Systems. UMAP (2012)
Alan Said, Brijnesh J. Jain, Andreas Lommatzsch, Sahin Albayrak
Correlating perception-oriented aspects in user-centric recommender system evaluation. IIiX (2012)
Alan Said, Brijnesh J. Jain, Sahin Albayrak
Analyzing weighting schemes in collaborative filtering: cold start, post cold start and power users. SAC (2012)
Brijnesh J. Jain, Klaus Obermayer
Extending Bron Kerbosch for Solving the Maximum Weight Clique Problem CoRR (2011)
Brijnesh J. Jain, Klaus Obermayer
Maximum Likelihood for Gaussians on Graphs. GbRPR (2011)
Brijnesh J. Jain, Klaus Obermayer
Generalized Learning Graph Quantization. GbRPR (2011)
Brijnesh J. Jain, Klaus Obermayer
Graph quantization. Comput. Vis. Image Underst. 115 (7) (2011)
Brijnesh J. Jain, Klaus Obermayer
Large Sample Statistics in the Domain of Graphs. SSPR/SPR (2010)
Brijnesh J. Jain, Klaus Obermayer
Consistent Estimator of Median and Mean Graph. ICPR (2010)
Brijnesh J. Jain, S. Deepak Srinivasan, Alexander Tissen, Klaus Obermayer
Learning Graph Quantization. SSPR/SPR (2010)
Johannes Mohr, Brijnesh J. Jain, Andreas Sutter, Antonius ter Laak, Thomas Steger-Hartmann, Nikolaus Heinrich, Klaus Obermayer
A Maximum Common Subgraph Kernel Method for Predicting the Chromosome Aberration Test. J. Chem. Inf. Model. 50 (10) (2010)
Brijnesh J. Jain, Klaus Obermayer
Graph Quantization CoRR (2010)
Brijnesh J. Jain, Klaus Obermayer
Accelerating Competitive Learning Graph Quantization CoRR (2010)
Brijnesh J. Jain, Klaus Obermayer
Elkan's k-Means Algorithm for Graphs. MICAI (2) (2010)
Brijnesh J. Jain, Klaus Obermayer
Algorithms for the Sample Mean of Graphs. CAIP (2009)
Brijnesh J. Jain, Klaus Obermayer
Bimal: Bipartite matching alignment for the contact map overlap problem. IJCNN (2009)
Brijnesh J. Jain, Brijnesh Stehr, Michael Lappe, Klaus Obermayer
Multiple alignment of contact maps. IJCNN (2009)
Brijnesh J. Jain, Klaus Obermayer
Structure Spaces. J. Mach. Learn. Res. 10 (2009)
Brijnesh J. Jain, Klaus Obermayer
Elkan's k-Means for Graphs CoRR (2009)
Brijnesh J. Jain, Klaus Obermayer
A Necessary and Sufficient Condition for Graph Matching Being Equivalent to the Maximum Weight Clique Problem CoRR (2009)
Brijnesh J. Jain, Klaus Obermayer
On the sample mean of graphs. IJCNN (2008)
Johannes Mohr, Brijnesh J. Jain, Klaus Obermayer
Molecule Kernels: A Descriptor- and Alignment-Free Quantitative Structure-Activity Relationship Approach. J. Chem. Inf. Model. 48 (9) (2008)
Brijnesh J. Jain, Michael Lappe
Joining Softassign and Dynamic Programming for the Contact Map Overlap Problem. BIRD (2007)
Brijnesh J. Jain, Fritz Wysotzki
Solving inexact graph isomorphism problems using neural networks. Neurocomputing 63 (2005)
Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki
SVM learning with the Schur-Hadamard inner product for graphs. Neurocomputing 64 (2005)
Brijnesh J. Jain, Fritz Wysotzki
Discrimination networks for maximum selection. Neural Networks 17 (1) (2004)
Brijnesh J. Jain, Fritz Wysotzki
Learning with Neural Networks in the Domain of Graphs. LWA (2004)
Barbara Hammer, Brijnesh J. Jain
Neural methods for non-standard data. ESANN (2004)
Peter Geibel, Brijnesh J. Jain, Fritz Wysotzki
SVM learning with the SH inner product. ESANN (2004)
Brijnesh J. Jain, Fritz Wysotzki
Structural Perceptrons for Attributed Graphs. SSPR/SPR (2004)
Brijnesh J. Jain, Fritz Wysotzki
The maximum weighted clique problem and Hopfield networks. ESANN (2004)
Brijnesh J. Jain, Peter Geibel, Fritz Wysotzki
Combining Recurrent Neural Networks and Support Vector Machines for Structural Pattern Recognition. KI (2004)
Brijnesh J. Jain, Fritz Wysotzki
Central Clustering of Attributed Graphs. Mach. Learn. 56 (1-3) (2004)
Brijnesh J. Jain, Fritz Wysotzki
A k-Winner-Takes-All Classifier for Structured Data. KI (2003)
Brijnesh J. Jain, Fritz Wysotzki
A Neural Graph Isomorphism Algorithm based on local Invariants. ESANN (2003)
Brijnesh J. Jain, Fritz Wysotzki
A Novel Neural Network Approach to Solve Exact and Inexact Graph Isomorphism Problems. ICANN (2003)
Brijnesh J. Jain, Fritz Wysotzki
A Competitive Winner-Takes-All Architecture for Classification and Pattern Recognition of Structures. GbRPR (2003)
Brijnesh J. Jain, Fritz Wysotzki
Automorphism Partitioning with Neural Networks. Neural Process. Lett. 17 (2) (2003)
Brijnesh J. Jain, Fritz Wysotzki
An Associative Memory for the Automorphism Group of Structures. ESANN (2003)
Brijnesh J. Jain, Fritz Wysotzki
Fast Winner-Takes-All Networks for the Maximum Clique Problem. KI (2002)
Brijnesh J. Jain, Fritz Wysotzki
On the short-term-memory of WTA nets. ESANN (2001)
Brijnesh J. Jain, Fritz Wysotzki
Efficient Pattern Discrimination with Inhibitory WTA Nets. ICANN (2001)