P. S. Sastry
According to our database1, P. S. Sastry authored at least 57 papers between 1988 and 2020.
Legend:Book In proceedings Article PhD thesis Other
On Robustness of Neural Architecture Search Under Label Noise.
Frontiers Big Data, 2020
Robust Learning of Multi-Label Classifiers under Label Noise.
Proceedings of the CoDS-COMAD 2020: 7th ACM IKDD CoDS and 25th COMAD, 2020
Discovering frequent chain episodes.
Knowl. Inf. Syst., 2019
PLUME: Polyhedral Learning Using Mixture of Experts.
Summarizing Event Sequences with Serial Episodes: A Statistical Model and an Application.
Efficient Learning of Restricted Boltzmann Machines Using Covariance Estimates.
Proceedings of The 11th Asian Conference on Machine Learning, 2019
Robust Loss Functions for Learning Multi-class Classifiers.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018
Multi-source Subnetwork-level Transfer in CNNs Using Filter-Trees.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018
Transfer Learning in CNNs Using Filter-Trees.
On the Robustness of Decision Tree Learning Under Label Noise.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017
Learning RBM with a DC programming Approach.
Proceedings of The 9th Asian Conference on Machine Learning, 2017
Robust Loss Functions under Label Noise for Deep Neural Networks.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017
Discovering compressing serial episodes from event sequences.
Knowl. Inf. Syst., 2016
Analyzing Similarities of Datasets Using a Pattern Set Kernel.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016
Bank of Weight Filters for Deep CNNs.
Proceedings of The 8th Asian Conference on Machine Learning, 2016
Inf. Sci., 2015
Statistical significance of episodes with general partial orders.
Inf. Sci., 2015
Making risk minimization tolerant to label noise.
Empirical Analysis of Sampling Based Estimators for Evaluating RBMs.
Proceedings of the Neural Information Processing - 22nd International Conference, 2015
Pattern set kernel.
Proceedings of the Second ACM IKDD Conference on Data Sciences, 2015
Noise Tolerance Under Risk Minimization.
IEEE Trans. Cybern., 2013
Pattern-growth based frequent serial episode discovery.
Data Knowl. Eng., 2013
Cloud Conveyors System: A Versatile Application for Exploring Cyber-Physical Systems.
Proceedings of the Control of Cyber-Physical Systems, 2013
Geometric Decision Tree.
IEEE Trans. Syst. Man Cybern. Part B, 2012
A unified view of the apriori-based algorithms for frequent episode discovery.
Knowl. Inf. Syst., 2012
Discovering injective episodes with general partial orders.
Data Min. Knowl. Discov., 2012
Polyceptron: A Polyhedral Learning Algorithm
A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces.
IEEE Trans. Syst. Man Cybern. Part B, 2010
Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains.
Neural Computation, 2010
Learning Polyhedral Classifiers Using Logistic Function.
Proceedings of the 2nd Asian Conference on Machine Learning, 2010
A unified view of Automata-based algorithms for Frequent Episode Discovery
Efficient Discovery of Large Synchronous Events in Neural Spike Streams
Multipath Dissemination in Regular Mesh Topologies.
IEEE Trans. Parallel Distrib. Syst., 2009
Temporal data mining for root-cause analysis of machine faults in automotive assembly lines
Discovering general partial orders in event streams
Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes.
A Geometric Algorithm for Learning Oblique Decision Trees.
Proceedings of the Pattern Recognition and Machine Intelligence, 2009
Inferring neuronal network connectivity from spike data: A temporal data mining approach.
Scientific Programming, 2008
Conditional probability based significance tests for sequential patterns in multi-neuronal spike trains
Inferring Neuronal Network Connectivity from Spike Data: A Temporal Datamining Approach
Discovering Frequent Generalized Episodes When Events Persist for Different Durations.
IEEE Trans. Knowl. Data Eng., 2007
A Feedback-Based Algorithm for Motion Analysis with Application to Object Tracking.
EURASIP J. Adv. Signal Process., 2007
Discovering Patterns in Multi-neuronal Spike Trains using the Frequent Episode Method
Inferring Neuronal Network Connectivity using Time-constrained Episodes
A fast algorithm for finding frequent episodes in event streams.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007
Network reconstruction from dynamic data.
SIGKDD Explorations, 2006
Discovering Frequent Episodes and Learning Hidden Markov Models: A Formal Connection.
IEEE Trans. Knowl. Data Eng., 2005
Two Timescale Analysis of the Alopex Algorithm for Optimization.
Neural Computation, 2002
A reinforcement learning neural network for adaptive control of Markov chains.
IEEE Trans. Syst. Man Cybern. Part A, 1997
Finite time analysis of the pursuit algorithm for learning automata.
IEEE Trans. Syst. Man Cybern. Part B, 1996
Memory neuron networks for identification and control of dynamical systems.
IEEE Trans. Neural Networks, 1994
Analysis of the back-propagation algorithm with momentum.
IEEE Trans. Neural Networks, 1994
Learning optimal conjunctive concepts through a team of stochastic automata.
IEEE Trans. Syst. Man Cybern., 1993
Surface reconstruction from disparate shading: an integration of shape-from-shading and stereopsis.
Proceedings of the 11th IAPR International Conference on Pattern Recognition, 1992
Simulation studies on the performance of an organizational model for graph reduction.
Future Gener. Comput. Syst., 1990
An SIMD machine for low-level vision.
Inf. Sci., 1988
A reduction architecture for the optimal scheduling of binary trees.
Future Gener. Comput. Syst., 1988