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2020 – today
- 2024
[c47]Tejas Duseja, K. M. Annervaz, Jeevithiesh Duggani, Shyam Zacharia, Michael Free, Ambedkar Dukkipati:
Learning to Switch off, Switch on, and Integrate Modalities in Large Pre-trained Transformers. MIPR 2024: 403-409- [c46]Rahul Venkataramani, Parag Dutta, Vikram Melapudi, Ambedkar Dukkipati:
Causal Feature Alignment: Learning to Ignore Spurious Background Features. WACV 2024: 4654-4662 - [i67]Tony Gracious, Ambedkar Dukkipati:
Interaction Event Forecasting in Multi-Relational Recursive HyperGraphs: A Temporal Point Process Approach. CoRR abs/2404.17943 (2024) - [i66]Ranga Shaarad Ayyagari, Anurita Ghosh, Ambedkar Dukkipati:
Temporal Abstraction in Reinforcement Learning with Offline Data. CoRR abs/2407.15241 (2024) - 2023
- [c45]Tony Gracious, Ambedkar Dukkipati:
Dynamic Representation Learning with Temporal Point Processes for Higher-Order Interaction Forecasting. AAAI 2023: 7748-7756 - [c44]Parag Dutta, Kawin Mayilvaghanan, Pratyaksha Sinha, Ambedkar Dukkipati:
Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain. ACML 2023: 343-358 - [c43]Ranga Shaarad Ayyagari, Ambedkar Dukkipati:
Risk-Averse Combinatorial Semi-Bandits. ISIT 2023: 1472-1477 - [c42]Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav V. Marathe, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Ambedkar Dukkipati, Tony Gracious, Shubham Gupta, Nihesh Rathod, Rajesh Sundaresan, Sarath Yasodharan, Kantha Rao Bhimala, Vidyadhar Mudkavi, Gopal Krishna Patra, Siva Athreya:
A Multi-Team Multi-Model Collaborative Covid-19 Forecasting Hub for India. WSC 2023: 994-1005 - [i65]Tony Gracious, Arman Gupta, Ambedkar Dukkipati:
Neural Temporal Point Process for Forecasting Higher Order and Directional Interactions. CoRR abs/2301.12210 (2023) - [i64]Ranga Shaarad Ayyagari, Ambedkar Dukkipati:
Markov Decision Process with an External Temporal Process. CoRR abs/2305.16056 (2023) - [i63]Parag Dutta, Kawin Mayilvaghanan, Pratyaksha Sinha, Ambedkar Dukkipati:
Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain. CoRR abs/2309.17009 (2023) - 2022
- [j15]Sourabh Balgi
, Ambedkar Dukkipati:
Contradistinguisher: A Vapnik's Imperative to Unsupervised Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 4730-4747 (2022) - [c41]Anoop Kumar, Vibha Balaji, M. A. Chandrashekar, Ambedkar Dukkipati, Sathish Vadhiyar:
Graph Convolutional Neural Networks for Alzheimer's Classification with Transfer Learning and HPC Methods. IPDPS Workshops 2022: 186-195 - [c40]Ambedkar Dukkipati, Rajarshi Banerjee, Ranga Shaarad Ayyagari, Dhaval Parmar Udaybhai:
Learning Skills to Navigate without a Master: A Sequential Multi-Policy Reinforcement Learning Algorithm. IROS 2022: 2483-2489 - [c39]Shubham Gupta, Ambedkar Dukkipati:
Consistency of Constrained Spectral Clustering under Graph Induced Fair Planted Partitions. NeurIPS 2022 - [i62]Shubham Gupta, Ambedkar Dukkipati:
On consistency of constrained spectral clustering under representation-aware stochastic block model. CoRR abs/2203.02005 (2022) - 2021
- [j14]Shubham Gupta, Gururaj K, Ambedkar Dukkipati, Rui M. Castro:
Equipping SBMs with RBMs: an interpretable approach for analysis of networks with covariates. J. Complex Networks 10(2) (2021) - [j13]Nilesh A. Kande, Rupali Dakhane, Ambedkar Dukkipati, Phaneendra K. Yalavarthy:
SiameseGAN: A Generative Model for Denoising of Spectral Domain Optical Coherence Tomography Images. IEEE Trans. Medical Imaging 40(1): 180-192 (2021) - [c38]Tony Gracious, Shubham Gupta, Arun Kanthali, Rui M. Castro, Ambedkar Dukkipati:
Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs. AAAI 2021: 4054-4062 - [c37]Rishi Hazra, Parag Dutta, Shubham Gupta, Mohammed Abdul Qaathir, Ambedkar Dukkipati:
Active² Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation. NAACL-HLT 2021: 1982-1995 - [i61]Ambedkar Dukkipati, Rajarshi Banerjee, Ranga Shaarad Ayyagari, Dhaval Parmar Udaybhai:
Stay Alive with Many Options: A Reinforcement Learning Approach for Autonomous Navigation. CoRR abs/2102.00168 (2021) - [i60]Shubham Gupta, Ambedkar Dukkipati:
Protecting Individual Interests across Clusters: Spectral Clustering with Guarantees. CoRR abs/2105.03714 (2021) - [i59]Ambedkar Dukkipati, Tony Gracious, Shubham Gupta:
CoviHawkes: Temporal Point Process and Deep Learning based Covid-19 forecasting for India. CoRR abs/2109.06056 (2021) - [i58]Ranga Shaarad Ayyagari, Ambedkar Dukkipati:
Risk-Aware Algorithms for Combinatorial Semi-Bandits. CoRR abs/2112.01141 (2021) - [i57]K. M. Annervaz, Pritam Kumar Nath, Ambedkar Dukkipati:
ActKnow: Active External Knowledge Infusion Learning for Question Answering in Low Data Regime. CoRR abs/2112.09423 (2021) - [i56]Tony Gracious, Ambedkar Dukkipati:
Representation Learning for Dynamic Hyperedges. CoRR abs/2112.10154 (2021) - [i55]Aayushee Gupta, K. M. Annervaz, Ambedkar Dukkipati, Shubhashis Sengupta:
An Inference Approach To Question Answering Over Knowledge Graphs. CoRR abs/2112.11070 (2021) - 2020
- [c36]Shubham Gupta, Rishi Hazra, Ambedkar Dukkipati:
Networked Multi-Agent Reinforcement Learning with Emergent Communication. AAMAS 2020: 1858-1860 - [c35]Shubham Gupta, Ambedkar Dukkipati:
Winning an Election: On Emergent Strategic Communication in Multi-Agent Networks. AAMAS 2020: 1861-1863 - [i54]Shubham Gupta, Rishi Hazra, Ambedkar Dukkipati:
Networked Multi-Agent Reinforcement Learning with Emergent Communication. CoRR abs/2004.02780 (2020) - [i53]Sourabh Balgi, Ambedkar Dukkipati:
Contradistinguisher: Applying Vapnik's Philosophy to Unsupervised Domain Adaptation. CoRR abs/2005.14007 (2020) - [i52]Tony Gracious, Ambedkar Dukkipati:
Adversarial Context Aware Network Embeddings for Textual Networks. CoRR abs/2011.02665 (2020) - [i51]Shaarad A. R, Ambedkar Dukkipati:
A Regret bound for Non-stationary Multi-Armed Bandits with Fairness Constraints. CoRR abs/2012.13380 (2020)
2010 – 2019
- 2019
- [c34]Shubham Gupta, Gaurav Sharma, Ambedkar Dukkipati:
A Generative Model for Dynamic Networks with Applications. AAAI 2019: 7842-7849 - [c33]Somnath Basu Roy Chowdhury, K. M. Annervaz, Ambedkar Dukkipati:
Instance-based Inductive Deep Transfer Learning by Cross-Dataset Querying with Locality Sensitive Hashing. DeepLo@EMNLP-IJCNLP 2019: 183-191 - [c32]Sourabh Balgi, Ambedkar Dukkipati:
CUDA: Contradistinguisher for Unsupervised Domain Adaptation. ICDM 2019: 21-30 - [c31]Akshay Mehrotra, Ambedkar Dukkipati:
Skip Residual Pairwise Networks With Learnable Comparative Functions for Few-Shot Learning. WACV 2019: 886-894 - [c30]Gaurav Pandey, Ambedkar Dukkipati:
Learning to Segment With Image-Level Supervision. WACV 2019: 1856-1865 - [i50]Shubham Gupta, Ambedkar Dukkipati:
On Voting Strategies and Emergent Communication. CoRR abs/1902.06897 (2019) - [i49]Sourabh Balgi, Ambedkar Dukkipati:
CUDA: Contradistinguisher for Unsupervised Domain Adaptation. CoRR abs/1909.03442 (2019) - [i48]Rishi Hazra, Shubham Gupta, Ambedkar Dukkipati:
Active Learning with Siamese Twins for Sequence Tagging. CoRR abs/1911.00234 (2019) - [i47]Shubham Gupta, Ambedkar Dukkipati, Rui M. Castro:
Restricted Boltzmann Stochastic Block Model: A Generative Model for Networks with Attributes. CoRR abs/1911.04172 (2019) - [i46]Shubham Gupta, Rui M. Castro, Ambedkar Dukkipati:
A Statistical Model for Dynamic Networks with Neural Variational Inference. CoRR abs/1911.11455 (2019) - 2018
- [j12]Maria Francis, Ambedkar Dukkipati:
On Gröbner bases and Krull dimension of residue class rings of polynomial rings over integral domains. J. Symb. Comput. 86: 1-19 (2018) - [c29]Muni Sreenivas Pydi, Ambedkar Dukkipati:
On Consistency of Compressive Spectral Clustering. ISIT 2018: 2102-2106 - [c28]K. M. Annervaz, Somnath Basu Roy Chowdhury, Ambedkar Dukkipati:
Learning beyond Datasets: Knowledge Graph Augmented Neural Networks for Natural Language Processing. NAACL-HLT 2018: 313-322 - [i45]Shubham Gupta, Gaurav Sharma, Ambedkar Dukkipati:
Evolving Latent Space Model for Dynamic Networks. CoRR abs/1802.03725 (2018) - [i44]K. M. Annervaz, Somnath Basu Roy Chowdhury, Ambedkar Dukkipati:
Learning beyond datasets: Knowledge Graph Augmented Neural Networks for Natural language Processing. CoRR abs/1802.05930 (2018) - [i43]Somnath Basu Roy Chowdhury, K. M. Annervaz, Ambedkar Dukkipati:
Instance-based Inductive Deep Transfer Learning by Cross-Dataset Querying with Locality Sensitive Hashing. CoRR abs/1802.05934 (2018) - 2017
- [j11]Debarghya Ghoshdastidar, Ambedkar Dukkipati:
Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques. J. Mach. Learn. Res. 18: 50:1-50:41 (2017) - [c27]Gaurav Pandey, Ambedkar Dukkipati:
Unsupervised Feature Learning with Discriminative Encoder. ICDM 2017: 367-376 - [c26]Pranav Shyam, Shubham Gupta, Ambedkar Dukkipati:
Attentive Recurrent Comparators. ICML 2017: 3173-3181 - [c25]Gaurav Pandey, Ambedkar Dukkipati:
Variational methods for conditional multimodal deep learning. IJCNN 2017: 308-315 - [i42]Ashwin Guha, Muni Sreenivas Pydi, Biswajit Paria, Ambedkar Dukkipati:
Analytic Connectivity in General Hypergraphs. CoRR abs/1701.04548 (2017) - [i41]Mahesh Gorijala, Ambedkar Dukkipati:
Image Generation and Editing with Variational Info Generative AdversarialNetworks. CoRR abs/1701.04568 (2017) - [i40]Gaurav Pandey, Ambedkar Dukkipati:
Discriminative Neural Topic Models. CoRR abs/1701.06796 (2017) - [i39]Muni Sreenivas Pydi, Ambedkar Dukkipati:
On Consistency of Compressive Spectral Clustering. CoRR abs/1702.03522 (2017) - [i38]Pranav Shyam, Shubham Gupta, Ambedkar Dukkipati:
Attentive Recurrent Comparators. CoRR abs/1703.00767 (2017) - [i37]Akshay Mehrotra, Ambedkar Dukkipati:
Generative Adversarial Residual Pairwise Networks for One Shot Learning. CoRR abs/1703.08033 (2017) - [i36]Gaurav Pandey, Ambedkar Dukkipati:
Amortized Inference and Learning in Latent Conditional Random Fields for Weakly-Supervised Semantic Image Segmentation. CoRR abs/1705.01262 (2017) - [i35]Gaurav Pandey, Ambedkar Dukkipati:
Unsupervised feature learning with discriminative encoder. CoRR abs/1709.00672 (2017) - 2016
- [j10]Debarghya Ghoshdastidar, Ajay P. Adsul, Ambedkar Dukkipati:
Learning With Jensen-Tsallis Kernels. IEEE Trans. Neural Networks Learn. Syst. 27(10): 2108-2119 (2016) - [c24]Gaurav Pandey, Ambedkar Dukkipati:
On collapsed representation of hierarchical Completely Random Measures. ICML 2016: 1605-1613 - [c23]Ambedkar Dukkipati, Debarghya Ghoshdastidar, Jinu Krishnan:
Mixture modeling with compact support distributions for unsupervised learning. IJCNN 2016: 2706-2713 - [i34]Maria Francis, Ambedkar Dukkipati:
A Gröbner Basis Algorithm for Computing the Krull Dimension of $A$-Algebras. CoRR abs/1602.04300 (2016) - [i33]Debarghya Ghoshdastidar, Ambedkar Dukkipati:
Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques. CoRR abs/1602.06516 (2016) - [i32]Gaurav Pandey, Ambedkar Dukkipati:
Variational methods for Conditional Multimodal Learning: Generating Human Faces from Attributes. CoRR abs/1603.01801 (2016) - [i31]Biswajit Paria, K. M. Annervaz, Ambedkar Dukkipati, Ankush Chatterjee, Sanjay Podder:
A Neural Architecture Mimicking Humans End-to-End for Natural Language Inference. CoRR abs/1611.04741 (2016) - [i30]Siddharth Agrawal, Ambedkar Dukkipati:
Deep Variational Inference Without Pixel-Wise Reconstruction. CoRR abs/1611.05209 (2016) - 2015
- [j9]Ashwin Guha, Ambedkar Dukkipati:
An Algorithmic Characterization of Polynomial Functions over Zpn. Algorithmica 71(1): 201-218 (2015) - [j8]Ambedkar Dukkipati, Nithish Pai, Maria Francis, Abhishek Dubey:
On Gröbner bases over rings and residue class polynomial rings with torsion. ACM Commun. Comput. Algebra 49(2): 60-61 (2015) - [j7]Ashwin Guha, Ambedkar Dukkipati:
A faster algorithm for testing polynomial representability of functions over finite integer rings. Theor. Comput. Sci. 579: 88-99 (2015) - [c22]Debarghya Ghoshdastidar, Ambedkar Dukkipati:
Spectral Clustering Using Multilinear SVD: Analysis, Approximations and Applications. AAAI 2015: 2610-2616 - [c21]Debarghya Ghoshdastidar, Ambedkar Dukkipati:
A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning. ICML 2015: 400-409 - [i29]Gaurav Pandey, Ambedkar Dukkipati:
Hierarchical Completely Random Measures for Mixed Membership Modelling. CoRR abs/1509.01817 (2015) - 2014
- [j6]Debarghya Ghoshdastidar, Ambedkar Dukkipati, Shalabh Bhatnagar:
Newton-based stochastic optimization using q-Gaussian smoothed functional algorithms. Autom. 50(10): 2606-2614 (2014) - [j5]Maria Francis, Ambedkar Dukkipati:
Reduced Gröbner bases and Macaulay-Buchberger Basis Theorem over Noetherian rings. J. Symb. Comput. 65: 1-14 (2014) - [j4]Debarghya Ghoshdastidar, Ambedkar Dukkipati, Shalabh Bhatnagar:
Smoothed Functional Algorithms for Stochastic Optimization Using q-Gaussian Distributions. ACM Trans. Model. Comput. Simul. 24(3): 17:1-17:26 (2014) - [c20]Gaurav Pandey, Ambedkar Dukkipati:
To go deep or wide in learning? AISTATS 2014: 724-732 - [c19]Debarghya Ghoshdastidar, Ambedkar Dukkipati, Ajay P. Adsul, Aparna S. Vijayan:
Spectral Clustering with Jensen-Type Kernels and Their Multi-point Extensions. CVPR 2014: 1472-1477 - [c18]Gaurav Pandey, Ambedkar Dukkipati:
Learning by Stretching Deep Networks. ICML 2014: 1719-1727 - [c17]Debarghya Ghoshdastidar, Ambedkar Dukkipati:
Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model. NIPS 2014: 397-405 - [i28]Gaurav Pandey, Ambedkar Dukkipati:
To go deep or wide in learning? CoRR abs/1402.5634 (2014) - [i27]Debarghya Ghoshdastidar, Ambedkar Dukkipati, Ajay P. Adsul, Aparna S. Vijayan:
Spectral Clustering with Jensen-type kernels and their multi-point extensions. CoRR abs/1403.4378 (2014) - [i26]Ambedkar Dukkipati, Nithish Pai, Maria Francis, Abhishek Dubey:
Macaulay-Buchberger Basis Theorem for Residue Class Rings with Torsion and Border Bases over Rings. CoRR abs/1405.0472 (2014) - [i25]Maria Francis, Ambedkar Dukkipati:
Generalized Hash Functions based on Multivariate Ideal Lattices. CoRR abs/1410.2011 (2014) - 2013
- [c16]Debarghya Ghoshdastidar, Ambedkar Dukkipati:
On Power-Law Kernels, Corresponding Reproducing Kernel Hilbert Space and Applications. AAAI 2013: 365-371 - [c15]Ambedkar Dukkipati, Gaurav Pandey, Debarghya Ghoshdastidar, Paramita Koley, D. M. V. Satya Sriram:
Generative Maximum Entropy Learning for Multiclass Classification. ICDM 2013: 141-150 - [c14]Gaurav Pandey, Ambedkar Dukkipati:
Minimum description length principle for maximum entropy model selection. ISIT 2013: 1521-1525 - [i24]Maria Francis, Ambedkar Dukkipati:
On Reduced Gröbner Basis and Macaulay-Buchberger Basis Theorem over Noetherian Rings. CoRR abs/1304.6889 (2013) - [i23]Debarghya Ghoshdastidar, Ambedkar Dukkipati, Shalabh Bhatnagar:
Newton based Stochastic Optimization using q-Gaussian Smoothed Functional Algorithms. CoRR abs/1311.2296 (2013) - [i22]Abhishek Dubey, Ambedkar Dukkipati:
Comprehensive Border Bases for Zero Dimensional Parametric Polynomial Ideals. CoRR abs/1312.0453 (2013) - 2012
- [j3]Ambedkar Dukkipati:
On maximum entropy and minimum KL-divergence optimization by Gröbner basis methods. Appl. Math. Comput. 218(23): 11674-11687 (2012) - [j2]Prabhanjan Vijendra Ananth, Ambedkar Dukkipati:
Complexity of Gröbner basis detection and border basis detection. Theor. Comput. Sci. 459: 1-15 (2012) - [c13]Prabhanjan Vijendra Ananth, Ambedkar Dukkipati:
An Algebraic Characterization of Rainbow Connectivity. CASC 2012: 12-21 - [c12]Debarghya Ghoshdastidar, Ambedkar Dukkipati, Shalabh Bhatnagar:
q-Gaussian based Smoothed Functional algorithms for stochastic optimization. ISIT 2012: 1059-1063 - [c11]A. Dinesh Kumar, Ambedkar Dukkipati:
A two stage selective averaging LDPC decoding. ISIT 2012: 2866-2870 - [i21]Jithin Vachery, Ambedkar Dukkipati:
On Shore and Johnson properties for a Special Case of Csiszár f-divergences. CoRR abs/1201.4285 (2012) - [i20]Debarghya Ghoshdastidar, Ambedkar Dukkipati, Shalabh Bhatnagar:
q-Gaussian based Smoothed Functional Algorithm for Stochastic Optimization. CoRR abs/1202.5665 (2012) - [i19]Ashwin Guha, Ambedkar Dukkipati:
An Algorithmic Characterization of Polynomial Functions over Z_{p^n}. CoRR abs/1203.1122 (2012) - [i18]Debarghya Ghoshdastidar, Ambedkar Dukkipati:
On q-Gaussian kernel and its Reproducing Kernel Hilbert Space. CoRR abs/1204.1800 (2012) - [i17]Gaurav Pandey, Ambedkar Dukkipati:
Minimum Description Length Principle for Maximum Entropy Model Selection. CoRR abs/1204.6423 (2012) - [i16]D. M. V. Satya Sriram, Gaurav Pandey, Debarghya Ghoshdastidar, Ambedkar Dukkipati, M. Narasimha Murty:
Maximum Entropy with Maximum J-Divergence Discrimination for Text Classification. CoRR abs/1205.0651 (2012) - [i15]Debarghya Ghoshdastidar, Ambedkar Dukkipati, Shalabh Bhatnagar:
Smoothed Functional Algorithms for Stochastic Optimization using q-Gaussian Distributions. CoRR abs/1206.4832 (2012) - 2011
- [c10]Prabhanjan Vijendra Ananth, Ambedkar Dukkipati:
Border basis detection is NP-complete. ISSAC 2011: 11-18 - [i14]Prabhanjan Vijendra Ananth, Ambedkar Dukkipati:
On Gröbner Basis Detection for Zero-dimensional Ideals. CoRR abs/1105.0433 (2011) - [i13]A. Dinesh Kumar, Ambedkar Dukkipati:
A Two Stage Selective Averaging LDPC Decoding. CoRR abs/1107.2867 (2011) - [i12]Joel George Manathara, Ambedkar Dukkipati, Debasish Ghose:
On Consensus under Polynomial Protocols. CoRR abs/1107.3584 (2011) - [i11]Joel George Manathara, Ambedkar Dukkipati, Debasish Ghose:
Tropical Algebraic approach to Consensus over Networks. CoRR abs/1109.0418 (2011) - [i10]Prabhanjan Vijendra Ananth, Ambedkar Dukkipati:
An Algebraic Characterization of Rainbow Connectivity. CoRR abs/1109.2291 (2011) - [i9]Hari Krishna Malladi, Ambedkar Dukkipati:
A Parallel Cylindrical Algebraic Decomposition Algorithm for Quantifier Elimination on Real Closed Fields. CoRR abs/1112.5352 (2011) - 2010
- [c9]Ambedkar Dukkipati, Joel George Manathara:
An Algebraic Implicitization and Specialization of Minimum KL-Divergence Models. CASC 2010: 85-96 - [c8]Ambedkar Dukkipati, Abhay Kumar Yadav, M. Narasimha Murty:
Maximum Entropy Model Based Classification with Feature Selection. ICPR 2010: 565-568 - [c7]Ambedkar Dukkipati:
On Kolmogorov-Nagumo averages and nonextensive entropy. ISITA 2010: 446-451 - [i8]Prabhanjan Vijendra Ananth, Ambedkar Dukkipati:
Border basis detection is NP-complete. CoRR abs/1011.6021 (2010)
2000 – 2009
- 2009
- [c6]Ambedkar Dukkipati:
Embedding maximum entropy models in algebraic varieties by Gröbner bases methods. ISIT 2009: 1904-1908 - 2008
- [i7]Ambedkar Dukkipati:
Towards algebraic methods for maximum entropy estimation. CoRR abs/0804.1083 (2008) - 2007
- [j1]Ambedkar Dukkipati, Shalabh Bhatnagar, M. Narasimha Murty:
Gelfand-Yaglom-Perez theorem for generalized relative entropy functionals. Inf. Sci. 177(24): 5707-5714 (2007) - [i6]Ambedkar Dukkipati:
Maximum Entropy in the framework of Algebraic Statistics: A First Step. CoRR abs/cs/0701117 (2007) - 2006
- [i5]Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar:
On Measure Theoretic definitions of Generalized Information Measures and Maximum Entropy Prescriptions. CoRR abs/cs/0601080 (2006) - [i4]Ambedkar Dukkipati:
Nonextensive Pythagoras' Theorem. CoRR abs/cs/0611030 (2006) - 2005
- [c5]Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar:
Information theoretic justification of Boltzmann selection and its generalization to Tsallis case. Congress on Evolutionary Computation 2005: 1667-1674 - [c4]Ambedkar Dukkipati, Narasimha Murty Musti, Shalabh Bhatnagar:
Properties of Kullback-Leibler cross-entropy minimization in nonextensive framework. ISIT 2005: 2374-2378 - [i3]Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar:
Uniqueness of Nonextensive entropy under Renyi's Recipe. CoRR abs/cs/0511078 (2005) - 2004
- [c3]Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar:
Cauchy annealing schedule: an annealing schedule for Boltzmann selection scheme in evolutionary algorithms. IEEE Congress on Evolutionary Computation 2004: 55-62 - [i2]Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar:
Generalized Evolutionary Algorithm based on Tsallis Statistics. CoRR cs.AI/0407037 (2004) - [i1]Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar:
Cauchy Annealing Schedule: An Annealing Schedule for Boltzmann Selection Scheme in Evolutionary Algorithms. CoRR cs.AI/0408055 (2004) - 2003
- [c2]Ambedkar Dukkipati, M. Narasimha Murty, Shalabh Bhatnagar:
Quotient evolutionary space: abstraction of evolutionary process w.r.t macroscopic properties. IEEE Congress on Evolutionary Computation 2003: 846-853 - 2002
- [c1]Ambedkar Dukkipati, M. Narasimha Murty:
Selection by parts: 'selection in two episodes' in evolutionary algorithms. IEEE Congress on Evolutionary Computation 2002: 657-662
Coauthor Index
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