P. S. Sastry

发表

An SIMD machine for low-level vision

Y. V. Venkatesh, K. R. Ramakrishnan, K. Banerjee, 1988, Inf. Sci..

On the Robustness of Decision Tree Learning Under Label Noise

Aritra Ghosh, Naresh Manwani, P. S. Sastry, 2017, PAKDD.

Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes pdf

P. S. Sastry, Casey Diekman, Kohinoor Dasgupta, 2009, ArXiv.

Multipath Dissemination in Regular Mesh Topologies

Kranthi Kumar Mamidisetty, P. S. Sastry, M. Duan, 2009, IEEE Transactions on Parallel and Distributed Systems.

Shivakumar Sastry, P. S. Sastry, A. Ibrahim, 2016, PAKDD.

Learning optimal conjunctive concepts through a team of stochastic automata

Kanagasabai Rajaraman, P. S. Sastry, S. R. Ranjan, 1993, IEEE Trans. Syst. Man Cybern..

Simulation studies on the performance of an organizational model for graph reduction

Y. V. Venkatesh, K. Ravikanth, P. S. Sastry, 1990, Future Gener. Comput. Syst..

Making risk minimization tolerant to label noise

Aritra Ghosh, Naresh Manwani, P. S. Sastry, 2014, Neurocomputing.

Discovering injective episodes with general partial orders

Raajay Viswanathan, Avinash Achar, P. S. Sastry, 2011, Data Mining and Knowledge Discovery.

Text-dependent speaker recognition using speaker specific compensation

P. S. Sastry, S. Laxman, 2003, TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region.

Statistical significance of episodes with general partial orders

Avinash Achar, P. S. Sastry, 2015, Inf. Sci..

Summarizing Event Sequences with Serial Episodes: A Statistical Model and an Application pdf

P. S. Sastry, Soumyajit Mitra, 2019, ArXiv.

Inferring neuronal network connectivity from spike data: A temporal data mining approach

Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan, 2008, Sci. Program..

Discovering frequent episodes and learning hidden Markov models: a formal connection

P. S. Sastry, K. P. Unnikrishnan, Srivatsan Laxman, 2005, IEEE Transactions on Knowledge and Data Engineering.

A reduction architecture for the optimal scheduling of binary trees

Y. V. Venkatesh, K. R. Ramakrishnan, K. Ravikanth, 1988, Future Gener. Comput. Syst..

Discovering Frequent Generalized Episodes When Events Persist for Different Durations

P. S. Sastry, K. P. Unnikrishnan, Srivatsan Laxman, 2007, IEEE Transactions on Knowledge and Data Engineering.

Network reconstruction from dynamic data

Naren Ramakrishnan, Ramasamy Uthurusamy, P. S. Sastry, 2006, SKDD.

Bank of Weight Filters for Deep CNNs

P. S. Sastry, Kalpathi Ramakrishnan, Suresh Kirthi Kumaraswamy, 2016, ACML.

Noise Tolerance Under Risk Minimization

Naresh Manwani, P. S. Sastry, P. Sastry, 2011, IEEE Transactions on Cybernetics.

Remotely Operated Vehicle (ROV) IRIS-SP for Underwater Inspection Tasks

Debasish Ghose, P. S. Sastry, Alok Sahu, 2017, 2017 14th IEEE India Council International Conference (INDICON).

Robust Loss Functions for Learning Multi-class Classifiers

P. S. Sastry, Himanshu Kumar, P. Sastry, 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Edge detection through a time-homogeneous markov chain

P. S. Sastry, Vivek S. Borkar, Uma S Rajan, 1998 .

Pattern-growth based frequent serial episode discovery

Avinash Achar, P. S. Sastry, A. Ibrahim, 2013, Data Knowl. Eng..

Robust Learning of Multi-Label Classifiers under Label Noise

Naresh Manwani, P. S. Sastry, Himanshu Kumar, 2020, COMAD/CODS.

Empirical Analysis of Sampling Based Estimators for Evaluating RBMs

P. S. Sastry, Vidyadhar Upadhya, 2015, ICONIP.

Robust Loss Functions under Label Noise for Deep Neural Networks

Aritra Ghosh, P. S. Sastry, Himanshu Kumar, 2017, AAAI.

K-plane regression pdf

Naresh Manwani, P. S. Sastry, P. Sastry, 2012, Inf. Sci..

A unified view of the apriori-based algorithms for frequent episode discovery

Avinash Achar, P. S. Sastry, Srivatsan Laxman, 2011, Knowledge and Information Systems.

Geometric Decision Tree

Naresh Manwani, P. S. Sastry, P. Sastry, 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Transfer Learning in CNNs Using Filter-Trees pdf

K. R. Ramakrishnan, P. S. Sastry, Suresh Kirthi Kumaraswamy, 2017, ArXiv.

A neural network based automatic generation control design through reinforcement learning

P. S. Nagendra Rao, P. S. Sastry, T. P. Imthias Ahamed, 2006 .

Cloud Conveyors System: A Versatile Application for Exploring Cyber-Physical Systems

Shivakumar Sastry, Michael S. Branicky, P. S. Sastry, 2013, CPSW@CISS.

A reinforcement learning neural network for adaptive control of Markov chains

P. S. Sastry, P. S. Sastry, G. Santharam, 1997, IEEE Trans. Syst. Man Cybern. Part A.

Pattern set kernel

Shivakumar Sastry, P. S. Sastry, A. Ibrahim, 2015, CoDS '15.

Efficient Discovery of Large Synchronous Events in Neural Spike Streams pdf

Raajay Viswanathan, P. S. Sastry, K. P. Unnikrishnan, 2010, ArXiv.

Learning Polyhedral Classifiers Using Logistic Function

Naresh Manwani, P. S. Sastry, P. Sastry, 2010, ACML.

A survey of temporal data mining

P. S. Sastry, Srivatsan Laxman, P. Sastry, 2006 .

On Robustness of Neural Architecture Search Under Label Noise

Qingquan Song, Xia Hu, P. S. Sastry, 2020, Frontiers in Big Data.

A Feedback based Algorithm for Motion Detection

P. S. Sastry, Shesha Shah, P Nayak, 2000 .

Two Timescale Analysis of the Alopex Algorithm for Optimization

P. S. Sastry, K. P. Unnikrishnan, M. Magesh, 2002, Neural Computation.

An Introduction to Support Vector Machines

P. S. Sastry, P. Sastry, 2002 .

Discovering general partial orders in event streams pdf

Avinash Achar, P. S. Sastry, Srivatsan Laxman, 2009, ArXiv.

Continuous Action Learning Automata for Pattern Recognition

P. S. Sastry, G. Santharam, Mal Thathachar, 1993 .

Adaptive Stochastic Algorithms for Pattern Classiﬁcation

P. S. Sastry, Mal Thathachar, P. Sastry, 2001 .

Efficient Learning of Restricted Boltzmann Machines Using Covariance estimates

P. S. Sastry, Vidyadhar Upadhya, 2019, ACML.

Polyceptron: A Polyhedral Learning Algorithm pdf

Naresh Manwani, P. S. Sastry, P. Sastry, 2011, ArXiv.

Multi-source Subnetwork-level Transfer in CNNs Using Filter-Trees

K. R. Ramakrishnan, P. S. Sastry, Suresh Kirthi Kumaraswamy, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Reinforcement learning controllers for automatic generation control in power systems having re-heat units with GRC and dead-band

P. S. Nagendra Rao, P. S. Sastry, T. P. Imthias Ahamed, 2006 .

Memory neuron networks for identification and control of dynamical systems

P. S. Sastry, K. P. Unnikrishnan, G. Santharam, 1994, IEEE Trans. Neural Networks.

Analysis of the back-propagation algorithm with momentum

P. S. Sastry, V. V. Phansalkar, V. V. Phansalkar, 1994, IEEE Trans. Neural Networks.

A New Algorithm for Learning Oblique Decision Trees

P. S. Sastry, Shesha Shah, P. Sastry, 1996 .

Temporal data mining for root-cause analysis of machine faults in automotive assembly lines pdf

P. S. Sastry, K. P. Unnikrishnan, Basel Shadid, 2009, ArXiv.

A fast algorithm for finding frequent episodes in event streams

P. S. Sastry, K. P. Unnikrishnan, Srivatsan Laxman, 2007, KDD '07.

A unified view of Automata-based algorithms for Frequent Episode Discovery pdf

Avinash Achar, P. S. Sastry, Srivatsan Laxman, 2010, ArXiv.

A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces

Naresh Manwani, P. S. Sastry, G. D. Nagendra, 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Discovering Patterns in Multi-neuronal Spike Trains using the Frequent Episode Method pdf

Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan, 2007, ArXiv.

PLUME: Polyhedral Learning Using Mixture of Experts pdf

Naresh Manwani, P. S. Sastry, Kulin Shah, 2019, ArXiv.

An Overview of Restricted Boltzmann Machines

P. S. Sastry, Vidyadhar Upadhya, P. Sastry, 2019, Journal of the Indian Institute of Science.

A Geometric Algorithm for Learning Oblique Decision Trees

Naresh Manwani, P. S. Sastry, 2009, PReMI.

A font and size-independent OCR system for printed Kannada documents using support vector machines

P. S. Sastry, T. V. Ashwin, P. Sastry, 2002 .

Learning Automata in Stochastic Games with Incomplete Information

P. S. Sastry, Mal Thathachar, 1991 .

Robust Learning of Classifiers in the Presence of Label Noise

Naresh Manwani, P. S. Sastry, 2017 .

A new reinforcement learning based automatic generation controller for hydro-thermal power systems

P. S. Sastry, P.S.N. Rao, T.P.I. Ahamed, 2003, TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region.

Inferring Neuronal Network Connectivity using Time-constrained Episodes pdf

Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan, 2007, ArXiv.

Discovering compressing serial episodes from event sequences

Shivakumar Sastry, P. S. Sastry, A. Ibrahim, 2015, Knowledge and Information Systems.

A reinforcement learning approach to automatic generation control

P. S. Nagendra Rao, P. S. Sastry, T. P. Imthias Ahamed, 2002 .

Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains

P. S. Sastry, K. P. Unnikrishnan, P. Sastry, 2008, Neural Computation.

Finite time analysis of the pursuit algorithm for learning automata

Kanagasabai Rajaraman, P. S. Sastry, P. Sastry, 1996, IEEE Trans. Syst. Man Cybern. Part B.

A Feedback-Based Algorithm for Motion Analysis with Application to Object Tracking

P. S. Sastry, Shesha Shah, P. Sastry, 2007, EURASIP J. Adv. Signal Process..

Adaptive Sample Selection for Robust Learning under Label Noise pdf

P. S. Sastry, Deep Patel, 2021, ArXiv.

Memorization in Deep Neural Networks: Does the Loss Function Matter? pdf

P. S. Sastry, Deep Patel, P. Sastry, 2021, PAKDD.

Object Tracking Using Motion Direction Detection

P. S. Sastry, Shesha Shah, P. Sastry, 2000 .

Generalized frequent episodes in Event Sequences

P. S. Sastry, Srivatsan Laxman, Kp Unnikrishnan, 2002 .

Stochastic networks for constraint satisfaction and optimization

P. S. Sastry, P. Sastry, 1990 .

Games of Learning Automata

P. S. Sastry, M. A. L. Thathachar, 2004 .