Journal and Refereed Conference Publications

Generative Adversarial Residual Pairwise Networks for
One Shot Learning
. (by A. Mehrotra and A. Dukkipati)
[arXiv]

Amortized Inference and Learning in Latent Conditional
Random Fields for WeaklySupervised Semantic Image
Segmentation
. (by G. Pandey and A. Dukkipati)
[arXiv]

Coloring Random Bipartite Hypergraphs. (by
D. Ghoshdastidar and A. Dukkipati)
[pdf] [arXiv]

Learning beyond datasets: Knowledge Graph Augmented
Neural Networks for Natural language Processing. (by
Annervaz K.M, S. Chowdhury and A. Dukkipati)
(Accepted) In Proceedings of NAACL HLT, 2018.

On Grobner bases and Krull dimension of residue class
rings of polynomial
rings over integral domains. (by M. Francis and A. Dukkipati)
Journal of Symbolic Computation 86:119, 2018.
[Link] [arXiv]

Unsupervised Feature Learning with Discriminative Encoder. (by G. Pandey and A. Dukkipati)
(Accepted) In Proceedings of the IEEE International Conference on Data Mining (ICDM): 2017.

Uniform Hypergraph Partitioning: Provable
Tensor Methods and Sampling Techniques. (by
D. Ghoshdastidar and A. Dukkipati)
The Journal of Machine Learning Research 18(50):141, 2017.
[arXiv]

Attentive Recurrent Comparators. (by P. Shyam,
S. Gupta and A. Dukkipati)
In Proceedings of the International Conference on Machine Learning (ICML):31733181, 2017.
[arXiv]

On Ideal Lattices, Grobner Bases and Generalized Hash
Functions. (by M. Francis and A. Dukkipati)
(Accepted in) Journal of Algebra and its Applications, 2017.
[arXiv]

Variational methods for conditional multimodal deep
learning. (by G. Pandey and A. Dukkipati)
In Proceedings of the International Joint Conference on Neural Networks (IJCNN): 2017.
[arXiv] [DEEPimagine]

Consistency of Spectral Hypergraph Partitioning under
Planted Partition Model. (by D. Ghoshdastidar and A. Dukkipati)
The Annals of Statistics 45(1):289315, 2017.
[bibtex] [pdf] [arXiv]

Primes of the form
${x}^{2}+d{y}^{2}$
with
$x\equiv 0\phantom{\rule{0.1em}{0ex}}\left(\mathrm{mod}\phantom{\rule{0.1em}{0ex}}N\right)$
or
$y\equiv 0\phantom{\rule{0.1em}{0ex}}\left(\mathrm{mod}\phantom{\rule{0.1em}{0ex}}N\right)$
. (by A. Dukkipati and S. Palimar)
Proc. Indian Acad. Sci. (Math. Sci.) 127(1): 3543, 2017. 
On Collapsed representations of hierarchical Completely Random
Measures. (by G. Pandey and A. Dukkipati)
In Proceedings of the 33rd International Conference on Machine Learning (ICML): 16051613, 2016.
[pdf]

Learning with JensenTsallis kernels. (by
D. Ghoshdastidar, A. Adsul and A. Dukkipati)
IEEE Transactions on Neural Networks and Learning Systems 27(10): 21082119, 2016.
[pdf]

Mixture Modeling with Compact Support Distributions for
Unsupervised Learning . (by A. Dukkipati, D. Ghoshdastidar and
J. Krishnan)
In Proceedings of the International Joint Conference on Neural Networks (IJCNN): 27062713, 2016.
[pdf]

A Provable Generalized Tensor
Spectral Method for Uniform Hypergraph
Partitioning. (by D. Ghoshdastidar and A. Dukkipati)
In Proceedings of the 32nd International Conference on Machine Learning (ICML), 2015.
[pdf]

A faster algorithm for testing
polynomial representability of functions over finite integer
rings. (by A. Guha and A. Dukkipati)
Theoretical Computer Science 579:88–99, 2015.
[bibtex] [arXiv]

An algorithmic characterization
of polynomial functions over Z_{p^n}. (by A. Guha and A. Dukkipati)
Algorithmica 71(1):201218, 2015.
[bibtex] [arXiv]
 Spectral Clustering using
Multilinear SVD: Analysis, Approximations and
Applications. (by D. Ghoshdastidar and A. Dukkipati)
In Proceedings of 29th AAAI Conference on Artificial Intelligence (AAAI): 26102616, 2015.
[pdf] 
Consistency of Spectral Partitioning
of Uniform Hypergraphs under Planted Partition
Model. (by D. Ghoshdastidar and A. Dukkipati)
In Advances in Neural Information Processing Systems (NIPS): 397405, 2014.
[pdf]

Newton based Stochastic Optimization using
qGaussian Smoothed Functional Algorithms. (by
D. Ghoshdastidar, A. Dukkipati and S. Bhatnagar)
Automatica 50(10):2606–2614, 2014.

Smoothed functional algorithms for
stochastic optimization using qGaussian
distributions. (by D. Ghoshdastidar, A. Dukkipati and S. Bhatnagar)
ACM Transactions on Modeling and Computer Simulation 24(3):126, 2014.

Learning by stretching deep networks. (by G. Pandey
and A. Dukkipati)
In Proceedings of the 31st International Conference on Machine Learning (ICML): 17191727, 2014.
[pdf]

Spectral clustering with
Jensentype kernels and their multipoint
extensions. (by D. Ghoshdastidar, A. Dukkipati, A. P. Adsul and A. S. Vijayan)
In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR): 14721477, 2014.
[pdf]
 To go deep or wide in learning? (by G. Pandey and A. Dukkipati)
In Proceedings of Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS): 724732, 2014.
[pdf]

Reduced Grobner bases and
MacaulayBuchberger basis theorem over Noetherian
rings. (by M. Francis and A. Dukkipati)
Journal of Symbolic Computation 65:114, 2014.
[bibtex] [Link] [arXiv]

Generative maximum entropy learning
for multiclass classification. (by 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. 141150, IEEE press, 2013. (Regular Paper)
[bibtex] [pdf]

Minimum description length
principle for maximum entropy model selection. (by
G. Pandey and A. Dukkipati)
In Proceedings of IEEE International Symposium on Information Theory (ISIT), pp. 15211525, IEEE press, 2013.
[bibtex] [pdf]

On power law kernels, corresponding
reproducing kernel Hilbert space and applications. (by
D. Ghoshdastidar and A. Dukkipati)
In Proceedings of 27th AAAI Conference on Artificial Intelligence (AAAI) 2013.
[bibtex] [pdf]

Complexity of Gröbner basis
detection and border basis detection. (by P. V. Ananth
and A. Dukkipati)
Theoretical Computer Science 459: 115, 2012.
[bibtex] [Link]

On maximum entropy and minimum
KLdivergence optimization by Gröbner basis
methods. (by A. Dukkipati)
Applied Mathematics and Computation 218: 1167411687, 2012.
[bibtex]

An algebraic characterization of
rainbow connectivity.
(by P. V. Ananth and A. Dukkipati)
V. P. Gerdt et al. (Eds.) In Proceedings of International Workshop on Computer Algebra in Scientific Computing (CASC): 1221, Springer Lecture Notes in Computer Science, 2012.
[bibtex]

qGaussian based smoothed
functional algorithms for stochastic optimization.(by
D. Ghoshdastidar, A. Dukkipati and S. Bhatnagar)
In Proceedings of IEEE International Symposium on Information Theory (ISIT): 10591063, IEEE press, 2012.

A two stage selective averaging LDPC decoding. (by
P. D. Kumar and A. Dukkipati)
In Proceedings of IEEE International Symposium on Information Theory (ISIT), pp. 28662870, IEEE press, 2012.

Border basis detection is NPcomplete. (by
P. V. Ananath and A. Dukkipati)
In Proceedings of ACM 36th International Symposium on Symbolic and Algebraic Computation (ISSAC): 1118, ACM 2011
[bibtex] [arXiv] [Link]

An algebraic implicitization
and specialization of minimum KLdivergence
models. (by A. Dukkipati and J. G. Manathara)
V. P. Gerdt et al. (Eds.) In Proceedings of International Workshop on Computer Algebra in Scientific Computing (CASC): 8596, Springer Lecture Notes in Computer Science, 2010.

On KolmogorovNagumo averages and nonextensive
entropy. (by A. Dukkipati)
In Proceedings of International Symposium on Information Theory and its Applications(ISITA), pp. 446451 IEEE press 2010.

Maximum entropy model based classification with feature
selection. (by A. Dukkipati, A. K. Yadav and M. N. Murty)
In Proceedings of IEEE International Conference on Pattern Recognition (ICPR), pp. 565568, IEEE press, 2010.

Embedding maximum entropy models in
algebraic varieties by Grobner bases methods. (by A. Dukkipati)
In Proceedings of IEEE International Symposium on Information Theory (ISIT), pp.19041908, IEEE press, 2009.
[bibtex] 
On measuretheoretic aspects of
nonextensive entropy functionals and corresponding
maximum entropy prescriptions.
(by A. Dukkipati, S. Bhatnagar and M. N. Murty)
Physica A: Statistical Mechanics and its Applications, 384:124138, 2007. [Link]

GelfandYaglomPerez theorem for generalized relative
entropy functionals. (by A. Dukkipati, S. Bhatnagar and M. N. Murty)
Information Sciences, 177:57075714, 2007.

Nonextensive triangle equality and
other properties of Tsallis
relativeentropy minimization. (by A. Dukkipati, M. N. Murty and S. Bhatnagar)
Physica A: Statistical Mechanics and its Applications, Vol. 361, pp 124138, 2006.

Information theoretic justification of Boltzmann selection
and its generalization to Tsallis case. (by A. Dukkipati, M. N. Murty
and S. Bhatnagar)
In Proceedings of IEEE Congress on Evolutionary Computation (CEC) . Vol. 2, pp. 16671674, IEEE press, 2005. pdf

Properties of KullbackLeibler crossentropy minimization in
nonextensive framework. (by A. Dukkipati, M. N. Murty and S. Bhatnagar)
In Proceedings of IEEE International Symposium on Information Theory (ISIT), pp. 23742378, IEEE press, 2005.
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