P. S. Sastry

86 papers A* 2A 1B 2C 4Journal 64Unranked 12
YearRankTypeTitle / Venue / Authors
2024 — conf
Breadth-First Search Approach for Mining Serial Episodes with Simultaneous Events.
COMAD/CODS
Santhosh B. Gandreti, A. Ibrahim, P. S. Sastry
2024 — conf
Efficient Depth-First Search Approach for Mining Frequent Chain Episodes.
COMAD/CODS (December)
Santhosh B. Gandreti, Chandan J., P. S. Sastry
2023 A conf
Adaptive Sample Selection for Robust Learning under Label Noise.
WACV
Deep Patel, P. S. Sastry
2023 — conf
Efficient Depth-First Search Approach for Mining Injective General Episodes.
COMAD/CODS
Santhosh B. Gandreti, P. S. Sastry
2022 J jnl
Learning Gaussian-Bernoulli RBMs Using Difference of Convex Functions Optimization.
IEEE Trans. Neural Networks Learn. Syst.
Vidyadhar Upadhya, P. S. Sastry
2021 J jnl
Adaptive Sample Selection for Robust Learning under Label Noise.
CoRR
Deep Patel, P. S. Sastry
2021 J jnl
Learning Gaussian-Bernoulli RBMs using Difference of Convex Functions Optimization.
CoRR
Vidyadhar Upadhya, P. S. Sastry
2021 — conf
Memorization in Deep Neural Networks: Does the Loss Function Matter?
PAKDD (2)
Deep Patel, P. S. Sastry
2021 J jnl
Memorization in Deep Neural Networks: Does the Loss Function matter?
CoRR
Deep Patel, P. S. Sastry
2020 J jnl
On Robustness of Neural Architecture Search Under Label Noise.
Frontiers Big Data
Yi-Wei Chen, Qingquan Song, Xi Liu, P. S. Sastry, Xia Hu
2020 — conf
Robust Learning of Multi-Label Classifiers under Label Noise.
COMAD/CODS
Himanshu Kumar, Naresh Manwani, P. S. Sastry
2019 J jnl
Discovering frequent chain episodes.
Knowl. Inf. Syst.
Avinash Achar, P. S. Sastry
2019 C conf
Efficient Learning of Restricted Boltzmann Machines Using Covariance Estimates.
ACML
Vidyadhar Upadhya, P. S. Sastry
2019 J jnl
PLUME: Polyhedral Learning Using Mixture of Experts.
CoRR
Kulin Shah, P. S. Sastry, Naresh Manwani
2019 J jnl
Summarizing Event Sequences with Serial Episodes: A Statistical Model and an Application.
CoRR
Soumyajit Mitra, P. S. Sastry
2018 J jnl
Efficient Learning of Restricted Boltzmann Machines Using Covariance estimates.
CoRR
Vidyadhar Upadhya, P. S. Sastry
2018 B conf
Multi-source Subnetwork-level Transfer in CNNs Using Filter-Trees.
IJCNN
Suresh Kirthi Kumaraswamy, P. S. Sastry, K. R. Ramakrishnan
2018 B conf
Robust Loss Functions for Learning Multi-class Classifiers.
SMC
Himanshu Kumar, P. S. Sastry
2017 C conf
Learning RBM with a DC programming Approach.
ACML
Vidyadhar Upadhya, P. S. Sastry
2017 J jnl
Learning RBM with a DC programming Approach.
CoRR
Vidyadhar Upadhya, P. S. Sastry
2017 — conf
On the Robustness of Decision Tree Learning Under Label Noise.
PAKDD (1)
Aritra Ghosh, Naresh Manwani, P. S. Sastry
2017 A* conf
Robust Loss Functions under Label Noise for Deep Neural Networks.
AAAI
Aritra Ghosh, Himanshu Kumar, P. S. Sastry
2017 J jnl
Robust Loss Functions under Label Noise for Deep Neural Networks.
CoRR
Aritra Ghosh, Himanshu Kumar, P. S. Sastry
2017 J jnl
Transfer Learning in CNNs Using Filter-Trees.
CoRR
Suresh Kirthi Kumaraswamy, P. S. Sastry, K. R. Ramakrishnan
2016 — conf
Analyzing Similarities of Datasets Using a Pattern Set Kernel.
PAKDD (1)
A. Ibrahim, P. S. Sastry, Shivakumar Sastry
2016 C conf
Bank of Weight Filters for Deep CNNs.
ACML
Suresh Kirthi Kumaraswamy, P. S. Sastry, Kalpathi Ramakrishnan
2016 J jnl
Discovering compressing serial episodes from event sequences.
Knowl. Inf. Syst.
A. Ibrahim, Shivakumar Sastry, P. S. Sastry
2016 J jnl
On the Robustness of Decision Tree Learning under Label Noise.
CoRR
Aritra Ghosh, Naresh Manwani, P. S. Sastry
2015 — conf
Empirical Analysis of Sampling Based Estimators for Evaluating RBMs.
ICONIP (2)
Vidyadhar Upadhya, P. S. Sastry
2015 J jnl
Empirical Analysis of Sampling Based Estimators for Evaluating RBMs.
CoRR
Vidyadhar Upadhya, P. S. Sastry
2015 J jnl
K-plane regression.
Inf. Sci.
Naresh Manwani, P. S. Sastry
2015 J jnl
Making risk minimization tolerant to label noise.
Neurocomputing
Aritra Ghosh, Naresh Manwani, P. S. Sastry
2015 — conf
Pattern set kernel.
CODS
A. Ibrahim, P. S. Sastry, Shivakumar Sastry
2015 J jnl
Statistical significance of episodes with general partial orders.
Inf. Sci.
Avinash Achar, P. S. Sastry
2014 J jnl
Discovering Compressing Serial Episodes from Event Sequences.
CoRR
A. Ibrahim, Shivakumar Sastry, P. S. Sastry
2014 J jnl
Making Risk Minimization Tolerant to Label Noise.
CoRR
Aritra Ghosh, Naresh Manwani, P. S. Sastry
2013 — conf
Cloud Conveyors System: A Versatile Application for Exploring Cyber-Physical Systems.
CPSW@CISS
Shivakumar Sastry, Michael S. Branicky, P. S. Sastry
2013 J jnl
Noise Tolerance Under Risk Minimization.
IEEE Trans. Cybern.
Naresh Manwani, P. S. Sastry
2013 J jnl
Pattern-growth based frequent serial episode discovery.
Data Knowl. Eng.
Avinash Achar, A. Ibrahim, P. S. Sastry
2012 J jnl
A unified view of the apriori-based algorithms for frequent episode discovery.
Knowl. Inf. Syst.
Avinash Achar, Srivatsan Laxman, P. S. Sastry
2012 J jnl
Discovering injective episodes with general partial orders.
Data Min. Knowl. Discov.
Avinash Achar, Srivatsan Laxman, Raajay Viswanathan, P. S. Sastry
2012 J jnl
Geometric Decision Tree.
IEEE Trans. Syst. Man Cybern. Part B
Naresh Manwani, P. S. Sastry
2012 J jnl
K-Plane Regression
CoRR
Naresh Manwani, P. S. Sastry
2011 J jnl
Noise Tolerance under Risk Minimization
CoRR
Naresh Manwani, P. S. Sastry
2011 J jnl
Polyceptron: A Polyhedral Learning Algorithm
CoRR
Naresh Manwani, P. S. Sastry
2010 J jnl
A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces.
IEEE Trans. Syst. Man Cybern. Part B
P. S. Sastry, G. D. Nagendra, Naresh Manwani
2010 J jnl
A unified view of Automata-based algorithms for Frequent Episode Discovery
CoRR
Avinash Achar, Srivatsan Laxman, P. S. Sastry
2010 J jnl
Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains.
Neural Comput.
P. S. Sastry, K. P. Unnikrishnan
2010 J jnl
Efficient Discovery of Large Synchronous Events in Neural Spike Streams
CoRR
Raajay Viswanathan, P. S. Sastry, K. P. Unnikrishnan
2010 C conf
Learning Polyhedral Classifiers Using Logistic Function.
ACML
Naresh Manwani, P. S. Sastry
2009 — conf
A Geometric Algorithm for Learning Oblique Decision Trees.
PReMI
Naresh Manwani, P. S. Sastry
2009 J jnl
Discovering general partial orders in event streams
CoRR
Avinash Achar, Srivatsan Laxman, V. Raajay, P. S. Sastry
2009 J jnl
Multipath Dissemination in Regular Mesh Topologies.
IEEE Trans. Parallel Distributed Syst.
Kranthi K. Mamidisetty, Minlan Duan, Shivakumar Sastry, P. S. Sastry
2009 — ed.
Pattern Recognition and Machine Intelligence, Third International Conference, PReMI 2009, New Delhi, India, December 16-20, 2009 Proceedings
PReMI
Santanu Chaudhury, Sushmita Mitra, C. A. Murthy, P. S. Sastry, Sankar K. Pal
2009 J jnl
Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes.
CoRR
Casey O. Diekman, Kohinoor Dasgupta, Vijay N. Nair, P. S. Sastry, K. P. Unnikrishnan
2009 J jnl
Temporal data mining for root-cause analysis of machine faults in automotive assembly lines
CoRR
Srivatsan Laxman, Basel Shadid, P. S. Sastry, K. P. Unnikrishnan
2008 J jnl
Conditional probability based significance tests for sequential patterns in multi-neuronal spike trains
CoRR
P. S. Sastry, K. P. Unnikrishnan
2008 J jnl
Inferring Neuronal Network Connectivity from Spike Data: A Temporal Datamining Approach
CoRR
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan
2008 J jnl
Inferring neuronal network connectivity from spike data: A temporal data mining approach.
Sci. Program.
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan
2007 J jnl
A Feedback-Based Algorithm for Motion Analysis with Application to Object Tracking.
EURASIP J. Adv. Signal Process.
Shesha Shah, P. S. Sastry
2007 A* conf
A fast algorithm for finding frequent episodes in event streams.
KDD
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
2007 J jnl
Discovering Frequent Generalized Episodes When Events Persist for Different Durations.
IEEE Trans. Knowl. Data Eng.
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
2007 J jnl
Discovering Patterns in Multi-neuronal Spike Trains using the Frequent Episode Method
CoRR
K. P. Unnikrishnan, Debprakash Patnaik, P. S. Sastry
2007 J jnl
Inferring Neuronal Network Connectivity using Time-constrained Episodes
CoRR
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan
2006 J jnl
Network reconstruction from dynamic data.
SIGKDD Explor.
K. P. Unnikrishnan, Naren Ramakrishnan, P. S. Sastry, Ramasamy Uthurusamy
2005 J jnl
Discovering Frequent Episodes and Learning Hidden Markov Models: A Formal Connection.
IEEE Trans. Knowl. Data Eng.
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
2004 J jnl
Fingerprint classification using a feedback-based line detector.
IEEE Trans. Syst. Man Cybern. Part B
Shesha Shah, P. S. Sastry
2002 J jnl
Two Timescale Analysis of the Alopex Algorithm for Optimization.
Neural Comput.
P. S. Sastry, M. Magesh, K. P. Unnikrishnan
2002 J jnl
Varieties of learning automata: an overview.
IEEE Trans. Syst. Man Cybern. Part B
M. A. L. Thathachar, P. S. Sastry
1999 J jnl
New algorithms for learning and pruning oblique decision trees.
IEEE Trans. Syst. Man Cybern. Part C
Shesha Shah, P. S. Sastry
1999 J jnl
Stochastic optimization over continuous and discrete variables with applications to concept learning under noise.
IEEE Trans. Syst. Man Cybern. Part A
K. Rajaraman, P. S. Sastry
1997 J jnl
A reinforcement learning neural network for adaptive control of Markov chains.
IEEE Trans. Syst. Man Cybern. Part A
G. Santharam, P. S. Sastry
1996 J jnl
Finite time analysis of the pursuit algorithm for learning automata.
IEEE Trans. Syst. Man Cybern. Part B
Kanagasabai Rajaraman, P. S. Sastry
1994 J jnl
Analysis of Stochastic Automata Algorithm for Relaxation Labeling.
IEEE Trans. Pattern Anal. Mach. Intell.
P. S. Sastry, M. A. L. Thathachar
1994 J jnl
Analysis of the back-propagation algorithm with momentum.
IEEE Trans. Neural Networks
Vijay V. Phansalkar, P. S. Sastry
1994 J jnl
Decentralized Learning of Nash Equilibria in Multi-Person Stochastic Games With Incomplete Information.
IEEE Trans. Syst. Man Cybern. Syst.
P. S. Sastry, Vijay V. Phansalkar, M. A. L. Thathachar
1994 J jnl
Memory neuron networks for identification and control of dynamical systems.
IEEE Trans. Neural Networks
P. S. Sastry, G. Santharam, K. P. Unnikrishnan
1993 J jnl
Learning optimal conjunctive concepts through a team of stochastic automata.
IEEE Trans. Syst. Man Cybern.
P. S. Sastry, Kanagasabai Rajaraman, S. R. Ranjan
1992 — conf
Surface reconstruction from disparate shading: an integration of shape-from-shading and stereopsis.
ICPR (1)
Subhashis Banerjee, P. S. Sastry, Y. V. Venkatesh
1990 J jnl
Simulation studies on the performance of an organizational model for graph reduction.
Future Gener. Comput. Syst.
K. Ravikanth, P. S. Sastry, Y. V. Venkatesh
1988 J jnl
A reduction architecture for the optimal scheduling of binary trees.
Future Gener. Comput. Syst.
K. Ravikanth, P. S. Sastry, K. R. Ramakrishnan, Y. V. Venkatesh
1988 J jnl
An SIMD machine for low-level vision.
Inf. Sci.
K. Banerjee, P. S. Sastry, K. R. Ramakrishnan, Y. V. Venkatesh
1987 J jnl
A hierarchical system of learning automata that can learn die globally optimal path.
Inf. Sci.
M. A. L. Thathachar, P. S. Sastry
1987 J jnl
Learning Optimal Discriminant Functions through a Cooperative Game of Automata.
IEEE Trans. Syst. Man Cybern.
Mandayam A. L. Thathachar, P. S. Sastry
1986 J jnl
Relaxation Labeling with Learning Automata.
IEEE Trans. Pattern Anal. Mach. Intell.
Mandayam A. L. Thathachar, P. S. Sastry
1985 J jnl
A new approach to the design of reinforcement schemes for learning automata.
IEEE Trans. Syst. Man Cybern.
M. A. L. Thathachar, P. S. Sastry