Debarghya Ghoshdastidar

发表

Near-Optimal Comparison Based Clustering pdf

Michael Perrot, Pascal Mattia Esser, Debarghya Ghoshdastidar, 2020, NeurIPS.

Practical methods for graph two-sample testing

Ulrike von Luxburg, Debarghya Ghoshdastidar, 2018, NeurIPS.

Mixture modeling with compact support distributions for unsupervised learning

Ambedkar Dukkipati, Debarghya Ghoshdastidar, Jinu Krishnan, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Spectral Clustering Using Multilinear SVD: Analysis, Approximations and Applications

Ambedkar Dukkipati, Debarghya Ghoshdastidar, Ambedkar Dukkipati, 2015, AAAI.

Learning With Jensen-Tsallis Kernels

Ambedkar Dukkipati, Debarghya Ghoshdastidar, Ajay P. Adsul, 2016, IEEE Transactions on Neural Networks and Learning Systems.

Newton-based stochastic optimization using q-Gaussian smoothed functional algorithms pdf

Shalabh Bhatnagar, Ambedkar Dukkipati, Debarghya Ghoshdastidar, 2013, Autom..

Foundations of Comparison-Based Hierarchical Clustering

Ulrike von Luxburg, Debarghya Ghoshdastidar, Michaël Perrot, 2019, NeurIPS.

On q-Gaussian kernel and its Reproducing Kernel Hilbert Space pdf

Ambedkar Dukkipati, Debarghya Ghoshdastidar, 2012, ArXiv.

Generative Maximum Entropy Learning for Multiclass Classification

Ambedkar Dukkipati, Gaurav Pandey, Debarghya Ghoshdastidar, 2012, 2013 IEEE 13th International Conference on Data Mining.

q-Gaussian based Smoothed Functional algorithms for stochastic optimization

Shalabh Bhatnagar, Ambedkar Dukkipati, Debarghya Ghoshdastidar, 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

Comparison-Based Nearest Neighbor Search pdf

Ulrike von Luxburg, Debarghya Ghoshdastidar, Siavash Haghiri, 2017, AISTATS.

Two-Sample Tests for Large Random Graphs Using Network Statistics

Ulrike von Luxburg, Alexandra Carpentier, Debarghya Ghoshdastidar, 2017, COLT.

Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model

Ambedkar Dukkipati, Debarghya Ghoshdastidar, Ambedkar Dukkipati, 2014, NIPS.

Smoothed Functional Algorithms for Stochastic Optimization Using q-Gaussian Distributions pdf

Shalabh Bhatnagar, Ambedkar Dukkipati, Debarghya Ghoshdastidar, 2012, TOMC.

A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning

Ambedkar Dukkipati, Debarghya Ghoshdastidar, Ambedkar Dukkipati, 2015, ICML.

On Power-Law Kernels, Corresponding Reproducing Kernel Hilbert Space and Applications

Ambedkar Dukkipati, Debarghya Ghoshdastidar, Ambedkar Dukkipati, 2012, AAAI.

Comparison bades nearest neighbor search

Ulrike von Luxburg, Debarghya Ghoshdastidar, Siavash Haghiri, 2017 .

Maximum Entropy with Maximum J-Divergence Discrimination for Text Classification pdf

M. Narasimha Murty, Ambedkar Dukkipati, Gaurav Pandey, 2012, ArXiv.

Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques

Ambedkar Dukkipati, Debarghya Ghoshdastidar, Ambedkar Dukkipati, 2016, J. Mach. Learn. Res..

On the optimality of kernels for high-dimensional clustering pdf

Debarghya Ghoshdastidar, Leena Chennuru Vankadara, D. Ghoshdastidar, 2019, AISTATS.

Spectral Clustering with Jensen-Type Kernels and Their Multi-point Extensions

Ambedkar Dukkipati, Debarghya Ghoshdastidar, Ajay P. Adsul, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Improvement on Incremental Spectral Clustering

Debarghya Ghoshdastidar, Nil Ayday, 2021, LWDA.

Causal Forecasting: Generalization Bounds for Autoregressive Models pdf

Dominik Janzing, Debarghya Ghoshdastidar, Lenon Minorics, 2021, ArXiv.

Graphon based Clustering and Testing of Networks: Algorithms and Theory pdf

Debarghya Ghoshdastidar, Leena Chennuru Vankadara, Mahalakshmi Sabanayagam, 2021, ICLR.

Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks pdf

Pascal Mattia Esser, Debarghya Ghoshdastidar, Leena Chennuru Vankadara, 2021, NeurIPS.

New Insights into Graph Convolutional Networks using Neural Tangent Kernels pdf

Debarghya Ghoshdastidar, Mahalakshmi Sabanayagam, Pascal Esser, 2021, ArXiv.

Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models pdf

Ulrike von Luxburg, Debarghya Ghoshdastidar, Sebastian Bordt, 2021, AISTATS.