Our Publications

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2024

• Causal Feature Alignment: Learning to Ignore Spurious Background Features.

  R. Venkataramani, P. Dutta, V. Melapudi and A. Dukkipati

  In IEEE Winter Conference on Applications of Computer Vision (WACV)

2023

• Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain

  P. Dutta, Kawin M., Pratyaksha S. and A. Dukkipati

  The 15th Asian Conference on Machine Learning (ACML)

• Risk-Aware Algorithms for Combinatorial Semi-Bandits

  R. S. Ayyagari and A. Dukkipati

  Proceedings of International Symposium on Information Theory (ISIT)

• Dynamic Representation Learning with Temporal Point Processes for Higher-Order Interaction Forecasting

  T. Gracious and A. Dukkipati

  Proceedings of 37th AAAI Conference on Artificial Intelligence (AAAI)

• A Multi-Team Multi-Model Collaborative COVID-19 Forecasting Hub for India

  A. Adiga, S. Athreya, K. Bhimala, A. Dukkipati, T. Gracious, S. Gupta, B. Hurt, G. Kaur, B. Lewis, M. Marathe, V. Mudkavi, G. Patra, N. Rathod, R. Sundaresan, S. Venkataramanan and S. Yasodharan

  In Proceedings of Winter Simulation Conference (WSC)

2022

• Consistency of Constrained Spectral Clustering under Graph Induced Fair Planted Partitions

  S. Gupta and A. Dukkipati

  Advances in Neural Information Processing Systems (NeurIPS 2023)

• Learning Skills to Navigate without a Master: A Sequential Multi-Policy Reinforcement Learning Algorithm

  A. Dukkipati, R. Banerjee, R. S. Ayyagari and D. P. Udaybhai

  IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

• Equipping SBMs with RBMs: An Explainable Approach for Analysis of Networks with Covariates

  S. Gupta, Gururaj K., A. Dukkipati and R. M. Castro

  Journal of Complex Networks

2021

• Contradistinguisher: A Vapnik’s Imperative to Unsupervised Domain Adaptation

  S. Balgi and A. Dukkipati

  IEEE Transactions on Pattern Analysis and Machine Intelligence

• Active² Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation

  R. Hazra, P. Dutta, S. Gupta, M. A. Qaathir and A. Dukkipati

  In Proceedings of 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT)

• Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs

  T. Gracious, S. Gupta, A. Kanthali, R. M. Castro and A. Dukkipati

  In Proceedings of 35rd AAAI Conference on Artificial Intelligence (AAAI)

• SiameseGAN: A Generative Model for Denoising of Spectral Domain Optical Coherence Tomography Images

  N. A. Kande, R. Dakhane, A. Dukkipati and P. K. Yalavarthy

  IEEE Transactions on Medical Imaging

2020

• Winning an Election: On Emergent Strategic Communication in Multi-Agent Networks

  S. Gupta and A. Dukkipati

  Conference on Autonomous Agents and Multi-Agent Systems

• Networked Multi-Agent Reinforcement Learning with Emergent Communication

  S. Gupta, R. Hazra and A. Dukkipati

  9th International Conference on Autonomous Agents and Multi-Agent Systems

2019

• Instance-based Inductive Deep Transfer Learning by Cross-Dataset Querying with Locality Sensitive Hashing

  S. R. Chowdhury, K. Annervaz and A. Dukkipati

  EMNLP Workshop on Deep Learning for Low-resource NLP

• CUDA : Contradistinguisher for Unsupervised Domain Adaptation

  S. Balgi and A. Dukkipati

  In Proceedings of the IEEE International Conference on Data Mining (ICDM)

• Skip Residual Pairwise Networks with Learnable Comparative Functions for Few-shot Learning

  A. Mehrotra and A. Dukkipati

  In IEEE Winter Conference on Applications of Computer Vision (WACV)

• A Generative Model for Dynamic Networks with Applications

  S. Gupta, G. Sharma and A. Dukkipati

  Proceedings of the AAAI Conference on Artificial Intelligence

• Learning to segment with image-level supervision using CRF-CNN

  G. Pandey and A. Dukkipati

  In IEEE Winter Conference on Applications of Computer Vision (WACV)

2018

• On Consistency of Compressive Spectral Clustering

  M. S. Pydi and A. Dukkipati

  In Proceedings of IEEE International Symposium on Information Theory (ISIT)

• Learning beyond datasets: Knowledge Graph Augmented Neural Networks for Natural language Processing

  K. Annervaz, S. R. Chowdhury and A. Dukkipati

  In Proceedings of NAACL HLT

2017

• Unsupervised Feature Learning with Discriminative Encoder.

  G. Pandey and A. Dukkipati

  In Proceedings of the IEEE International Conference on Data Mining (ICDM)

• Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques

  D. Ghoshdastidar and A. Dukkipati

  Journal of Machine Learning Research

• Attentive Recurrent Comparators

  P. Shyam, S. Gupta and A. Dukkipati

  In Proceedings of the International Conference on Machine Learning (ICML), 2017

• Consistency of Spectral Hypergraph Partitioning under Planted Partition Model

  D. Ghoshdastidar and A. Dukkipati

  The Annals of Statistics

• Variational methods for conditional multimodal deep learning

  G. Pandey and A. Dukkipati

  Proceedings of the International Joint Conference on Neural Networks (IJCNN

2016

• On Collapsed representations of hierarchical Completely Random Measures.

  G. Pandey and A. Dukkipati

  Proceedings of the 33rd International Conference on Machine Learning (ICML):

• Mixture Modelling with Compact Support Distributions for Unsupervised Learning.

  A. Dukkipati, D. Ghoshdastidar and J. Krishnan

  Proceedings of the International Joint Conference on Neural Networks (IJCNN)

• Learning With Jensen-Tsallis Kernels

  D. Ghoshdastidar, A. P. Adsul and A. Dukkipati

  IEEE Transactions on Neural Networks and Learning Systems

2015

• A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning

  D. Ghoshdastidar and A. Dukkipati

  Proceedings of the 32nd International Conference on Machine Learning (ICML)

• Spectral Clustering Using Multilinear SVD: Analysis, Approximations and Applications

  D. Ghoshdastidar and A. Dukkipati

  Twenty-Ninth AAAI Conference on Artificial Intelligence

2014

• Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model

  D. Ghoshdastidar and A. Dukkipati

  Advances in Neural Information Processing Systems 27 (NIPS 2014)

• Newton based Stochastic Optimization using q-Gaussian Smoothed Functional Algorithms

  D. Ghoshdastidar, A. Dukkipati and S. Bhatnagar

  Automatica, 50(10):2606–2614

• Smoothed Functional Algorithms for Stochastic Optimization using q-Gaussian Distributions

  D. Ghoshdastidar, A. Dukkipati and S. Bhatnagar

  ACM Transactions on Modeling and Computer Simulation, 24 (3), Article 17,

• Learning by Stretching Deep Networks

  G. Pandey and A. Dukkipati

  Proceedings of the 31st International Conference on Machine Learning, PMLR 32(2):1719-1727

• Spectral Clustering with Jensen-type kernels and their multi-point extensions.

  D. Ghoshdastidar, A. Dukkipati, A. P. Adsul and A. S. Vijayan

  In Proceedings of Computer Vision and Pattern Recognition

• To go deep or wide in learning?

  G. Pandey and A. Dukkipati

  Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, PMLR 33:724-732

2013

• Generative Maximum Entropy Learning for Multiclass Classification

  A. Dukkipati, G. Pandey, D. Ghoshdastidar, P. Koley and D. S. Sriram

  Proceedings of IEEE International Conference on Data Mining (ICDM'13), pp. 141-150, IEEE press

• Minimum Description Length Principle for Maximum Entropy Model Selection

  G. Pandey and A. Dukkipati

  Proceedings of IEEE International Symposium on Information Theory (ISIT'13), pp. 1521-1525, IEEE press

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

  D. Ghoshdastidar and A. Dukkipati

  Proceedings of the AAAI Conference on Artificial Intelligence, 27

2012

• q-Gaussian based Smoothed Functional Algorithm for Stochastic Optimization

  D. Ghoshdastidar, A. Dukkipati and S. Bhatnagar

  Proceedings of IEEE International Symposium on Information Theory (ISIT'12), pp. 1059-1063, IEEE press

• A two stage selective averaging LDPC decoding

  A. Kumar and A. Dukkipati

  Proceedings of IEEE International Symposium on Information Theory (ISIT'12), pp. 2866-2870, IEEE press,

2010

• On Kolmogorov-Nagumo averages and nonextensive entropy

  A. Dukkipati

  International Symposium On Information Theory & Its Applications

• Maximum Entropy Model Based Classification with Feature Selection

  A. Dukkipati, A. K. Yadav and M. Murty

  20th International Conference on Pattern Recognition