Journal and Refereed Conference Publications
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Markov Decision Process with an External Temporal Process
R. S. Ayyagari and A. Dukkipati
[arXiv]
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A Regret bound for Nonstationary Multi-Armed Bandits with Fairness Constraints
R. S. Ayyagari and A. Dukkipati
[arXiv]
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Causal Feature Alignment: Learning to Ignore Spurious Background Features
R. Venkataramnai, P. Dutta, V. Melapudi and A. Dukkipati
WACV: 2024.
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Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain
P. Dutta, Kawin M, P. Sinha and A. Dukkipati
ACML: 2023.
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Risk-Aware Algorithms for Combinatorial Semi-Bandits
R. S. Ayyagari and A. Dukkipati
International Symposium on Information Theory (ISIT): 2023.
[arXiv]
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A Multi-Team Multi-Model Collaborative COVID-19 Forecasting Hub for India
A. Adiga, S. Athreya, K. R. Bhimala, A. Dukkipati, T. Gracious, S. Gupta, B. Hurt, G. Kaur, B. Lewis, M. Marathe, V. Mudkavi, G. K. Patra, N. Rathod, R. Sundaresan, S. Venkataramanans and S. Yasodharan
Winter Simulation Conference (WSC): 2023.
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Dynamic Representation Learning with Temporal Point Processes for Higher-Order Interaction Forecasting.
T. Gracious and A. Dukkipati
37th AAAI Conference on Artificial Intelligence (AAAI): 2023.
[pdf] -
Consistency of Constrained Spectral Clustering under Graph Induced Fair Planted Partitions.
S Gupta and A. Dukkipati
Conference on Neural Inforation Processing Systems (NeurIPS): 2022. [arXiv]
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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): 2022. [arXiv]
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Graph Convolutional Neural Networks for Alzheimer's Classification with Transfer Learning and HPC methods
A. Kumar, V. Balaji, M. A. Chandrashekar, A. Dukkipati, S. Vadhiyar
IPDPS Workshops 2022.
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Equipping SBMs with RBMs: An interpretable approach for analysis of networks with covariates.
S. Gupta, Gururaj K, A. Dukkipati and R. M. Castro
Journal of Complex Networks 10(2) 2022.
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Contradistinguisher: A Vapnik's Imperative to Unsupervised Domain Adaptation.
S. Balgi and A. Dukkipati
IEEE Transactions on Pattern Analysis and Machine Intelligence ,44(9):4730-4747, 2022. [pdf]
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Active^2 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 NAACL: 2021.
[arXiv]
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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 35th AAAI Conference on Artificial Intelligence (AAAI): 2021.
[pdf]
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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 40(1):180-192, 2021. [pdf]
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Winning an Election: On Emergent Strategic Communication in Multi-Agent Networks
S. Gupta and A. Dukkipati
In AAMAS: 2020.
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Networked Multi-Agent Reinforcement Learning with Emergent Communication
S. Gupta, R. Hazra and A. Dukkipati
In AAMAS: 2020.
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CUDA : Contradistinguisher for Unsupervised Domain Adaptation
S. Balgi and A. Dukkipati
In Proceedings of the IEEE International Conference on Data Mining (ICDM): 2019.
[arXiv]
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Instance-based Inductive Deep Transfer Learning by Cross-Dataset Querying with Locality Sensitive Hashing.
S. Chowdhury, Annervaz K. M and A. Dukkipati.
In EMNLP Workshop on Deep Learning for Low-resource NLP : 2019.
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A generative model for dynamic networks with
applications.
S. Gupta, G. Sharma and A. Dukkipati
In Proceedings of 33rd AAAI Conference on Artificial Intelligence (AAAI): 2019.
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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): 2019.
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Learning to segment with image-level supervision.
G. Pandey and A. Dukkipati
In IEEE Winter Conference on Applications of Computer Vision (WACV): 2019.
[arXiv] -
On Consistency of Compressive Spectral Clustering.
M. S. Pydi and A. Dukkipati
In Proceedings of IEEE International Symposium on Information Theory (ISIT): 2102-2106, 2018.
[arXiv]
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Learning beyond datasets: Knowledge Graph Augmented
Neural Networks for Natural language Processing.
Annervaz K.M, S. Chowdhury and A. Dukkipati
In Proceedings of NAACL HLT: 313-322, 2018.
[pdf] [blog]
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On Grobner bases and Krull dimension of residue class
rings of polynomial
rings over integral domains.
M. Francis and A. Dukkipati
Journal of Symbolic Computation 86:1-19, 2018. [Link] [arXiv]
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On Ideal Lattices, Grobner Bases and Generalized Hash
Functions.
M. Francis and A. Dukkipati
Journal of Algebra and its Applications 17 (06):1850112, 2018. [arXiv] -
Unsupervised Feature Learning with Discriminative
Encoder.
G. Pandey and A. Dukkipati
In Proceedings of the IEEE International Conference on Data Mining (ICDM):367-376, 2017.
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Uniform Hypergraph Partitioning: Provable
Tensor Methods and Sampling Techniques.
D. Ghoshdastidar and A. Dukkipati
The Journal of Machine Learning Research 18(50):1-41, 2017.
[arXiv]
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Attentive Recurrent Comparators.
P. Shyam, S. Gupta and A. Dukkipati
In Proceedings of the International Conference on Machine Learning (ICML):3173-3181, 2017.
[arXiv] [blog]
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Variational methods for conditional multimodal deep
learning.
G. Pandey and A. Dukkipati
In Proceedings of the International Joint Conference on Neural Networks (IJCNN): 2017.
[arXiv] [DEEPimagine]
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Consistency of Spectral Hypergraph Partitioning under
Planted Partition Model.
D. Ghoshdastidar and A. Dukkipati
The Annals of Statistics 45(1):289-315, 2017.
[bibtex] [pdf] [arXiv]
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Primes of the form
with
or
.
A. Dukkipati and S. Palimar
Proc. Indian Acad. Sci. (Math. Sci.) 127(1): 35-43, 2017. -
On Collapsed representations of hierarchical Completely Random
Measures.
G. Pandey and A. Dukkipati
In Proceedings of the 33rd International Conference on Machine Learning (ICML): 1605-1613, 2016.
[pdf]
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Learning with Jensen-Tsallis kernels.
D. Ghoshdastidar, A. Adsul and A. Dukkipati
IEEE Transactions on Neural Networks and Learning Systems 27(10): 2108-2119, 2016.
[pdf]
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Mixture Modeling with Compact Support Distributions for
Unsupervised Learning .
A. Dukkipati, D. Ghoshdastidar and J. Krishnan
In Proceedings of the International Joint Conference on Neural Networks (IJCNN): 2706-2713, 2016.
[pdf]
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A Provable Generalized Tensor
Spectral Method for Uniform Hypergraph
Partitioning.
D. Ghoshdastidar and A. Dukkipati
In Proceedings of the 32nd International Conference on Machine Learning (ICML), 2015.
[pdf]
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A faster algorithm for testing
polynomial representability of functions over finite integer
rings.
A. Guha and A. Dukkipati
Theoretical Computer Science 579:88–99, 2015.
[bibtex] [arXiv]
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An algorithmic characterization
of polynomial functions over Z_{p^n}.
A. Guha and A. Dukkipati
Algorithmica 71(1):201-218, 2015.
[bibtex] [arXiv]
- Spectral Clustering using
Multilinear SVD: Analysis, Approximations and
Applications.
D. Ghoshdastidar and A. Dukkipati
In Proceedings of 29th AAAI Conference on Artificial Intelligence (AAAI): 2610-2616, 2015.
[pdf] -
Consistency of Spectral Partitioning
of Uniform Hypergraphs under Planted Partition
Model.
D. Ghoshdastidar and A. Dukkipati
In Advances in Neural Information Processing Systems (NIPS): 397-405, 2014. [pdf]
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Newton based Stochastic Optimization using
q-Gaussian Smoothed Functional Algorithms.
D. Ghoshdastidar, A. Dukkipati and S. Bhatnagar
Automatica 50(10):2606–2614, 2014.
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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):1-26, 2014.
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Learning by stretching deep networks.
G. Pandey and A. Dukkipati
In Proceedings of the 31st International Conference on Machine Learning (ICML): 1719-1727, 2014.
[pdf]
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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 IEEE Conference on Computer Vision and Pattern Recognition (CVPR): 1472-1477, 2014. [pdf]
- To go deep or wide in learning?
G. Pandey and A. Dukkipati
In Proceedings of Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS): 724-732, 2014. [pdf]
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Reduced Grobner bases and
Macaulay-Buchberger basis theorem over Noetherian
rings.
M. Francis and A. Dukkipati
Journal of Symbolic Computation 65:1-14, 2014. [bibtex] [Link] [arXiv]
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Generative maximum entropy learning
for multiclass classification.
A. Dukkipati, G. Pandey, D. Ghoshdastidar, P. Koley and D. M. V. S. Sriram
In Proceedings of IEEE International Conference on Data Mining (ICDM), pp. 141-150, IEEE press, 2013. (Regular Paper) [bibtex] [pdf]
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Minimum description length
principle for maximum entropy model selection.
G. Pandey and A. Dukkipati
In Proceedings of IEEE International Symposium on Information Theory (ISIT), pp. 1521-1525, IEEE press, 2013.
[bibtex] [pdf]
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On power law kernels, corresponding
reproducing kernel Hilbert space and applications.
D. Ghoshdastidar and A. Dukkipati
In Proceedings of 27th AAAI Conference on Artificial Intelligence (AAAI) 2013.
[bibtex] [pdf]
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Complexity of Gröbner basis
detection and border basis detection.
P. V. Ananth and A. Dukkipati
Theoretical Computer Science 459: 1-15, 2012.
[bibtex] [Link]
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On maximum entropy and minimum
KL-divergence optimization by Gröbner basis
methods.
A. Dukkipati
Applied Mathematics and Computation 218: 11674-11687, 2012.
[bibtex]
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An algebraic characterization of
rainbow connectivity.
P. V. Ananth and A. Dukkipati
V. P. Gerdt et al. (Eds.) In Proceedings of International Workshop on Computer Algebra in Scientific Computing (CASC): 12-21, Springer Lecture Notes in Computer Science, 2012.
[bibtex]
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q-Gaussian based smoothed
functional algorithms for stochastic optimization.
D. Ghoshdastidar, A. Dukkipati and S. Bhatnagar
In Proceedings of IEEE International Symposium on Information Theory (ISIT): 1059-1063, IEEE press, 2012.
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A two stage selective averaging LDPC decoding.
P. D. Kumar and A. Dukkipati
In Proceedings of IEEE International Symposium on Information Theory (ISIT), pp. 2866-2870, IEEE press, 2012.
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Border basis detection is NP-complete.
P. V. Ananath and A. Dukkipati
In Proceedings of ACM 36th International Symposium on Symbolic and Algebraic Computation (ISSAC): 11-18, ACM 2011
[bibtex] [arXiv] [Link]
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An algebraic implicitization
and specialization of minimum KL-divergence
models.
A. Dukkipati and J. G. Manathara
V. P. Gerdt et al. (Eds.) In Proceedings of International Workshop on Computer Algebra in Scientific Computing (CASC): 85-96, Springer Lecture Notes in Computer Science, 2010.
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On Kolmogorov-Nagumo averages and nonextensive
entropy.
A. Dukkipati
In Proceedings of International Symposium on Information Theory and its Applications(ISITA), pp. 446-451 IEEE press 2010.
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Maximum entropy model based classification with feature
selection.
A. Dukkipati, A. K. Yadav and M. N. Murty
In Proceedings of IEEE International Conference on Pattern Recognition (ICPR), pp. 565-568, IEEE press, 2010.
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Embedding maximum entropy models in
algebraic varieties by Grobner bases methods.
A. Dukkipati
In Proceedings of IEEE International Symposium on Information Theory (ISIT), pp.1904-1908, IEEE press, 2009.
[bibtex] -
On measure-theoretic aspects of
nonextensive entropy functionals and corresponding
maximum entropy prescriptions.
A. Dukkipati, S. Bhatnagar and M. N. Murty
Physica A: Statistical Mechanics and its Applications, 384:124-138, 2007. [Link]
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Gelfand-Yaglom-Perez theorem for generalized relative
entropy functionals.
A. Dukkipati, S. Bhatnagar and M. N. Murty
Information Sciences, 177:5707-5714, 2007.
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Nonextensive triangle equality and
other properties of Tsallis
relative-entropy minimization.
A. Dukkipati, M. N. Murty and S. Bhatnagar
Physica A: Statistical Mechanics and its Applications, Vol. 361, pp 124-138, 2006.
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Information theoretic justification of Boltzmann selection
and its generalization to Tsallis case.
A. Dukkipati, M. N. Murty and S. Bhatnagar
In Proceedings of IEEE Congress on Evolutionary Computation (CEC) . Vol. 2, pp. 1667-1674, IEEE press, 2005. pdf
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Properties of Kullback-Leibler cross-entropy minimization in
nonextensive framework.
A. Dukkipati, M. N. Murty and S. Bhatnagar
In Proceedings of IEEE International Symposium on Information Theory (ISIT), pp. 2374--2378, IEEE press, 2005.
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Technical Reports and Unpublished Papers
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CoviHawkes: Temporal Point Process and Deep Learning based Covid-19 forecasting for India. (by A. Dukkipati, T. Gracious and S. Gupta)
2021.
arXiv
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Tropical algebraic approach to
consensus over networks. (by J. G. Manathara, A. Dukkipati and D. Ghose)
2011.
arXiv
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On parametric and implicit algebraic
descriptions of maximum entropy models. (by A. Dukkipati)
EURANDOM report 2008-038, 2008.
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