P. S. Sastry

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 26

Top Topics

Neural Architecture

Statistical Significance

Efficient Learning

Top Venues

Knowl. Inf. Syst.

Publications

Santhosh B. Gandreti, Ibrahim A., P. S. Sastry
Breadth-First Search Approach for Mining Serial Episodes with Simultaneous Events. COMAD/CODS (2024)
Deep Patel, P. S. Sastry
Adaptive Sample Selection for Robust Learning under Label Noise. WACV (2023)
Vidyadhar Upadhya, P. S. Sastry
Learning Gaussian-Bernoulli RBMs Using Difference of Convex Functions Optimization. IEEE Trans. Neural Networks Learn. Syst. 33 (10) (2022)
Deep Patel, P. S. Sastry
Memorization in Deep Neural Networks: Does the Loss Function Matter? PAKDD (2) (2021)
Deep Patel, P. S. Sastry
Memorization in Deep Neural Networks: Does the Loss Function matter? CoRR (2021)
Deep Patel, P. S. Sastry
Adaptive Sample Selection for Robust Learning under Label Noise. CoRR (2021)
Vidyadhar Upadhya, P. S. Sastry
Learning Gaussian-Bernoulli RBMs using Difference of Convex Functions Optimization. CoRR (2021)
Yi-Wei Chen, Qingquan Song, Xi Liu, P. S. Sastry, Xia Hu
On Robustness of Neural Architecture Search Under Label Noise. Frontiers Big Data 3 (2020)
Himanshu Kumar, Naresh Manwani, P. S. Sastry
Robust Learning of Multi-Label Classifiers under Label Noise. COMAD/CODS (2020)
Soumyajit Mitra, P. S. Sastry
Summarizing Event Sequences with Serial Episodes: A Statistical Model and an Application. CoRR (2019)
Avinash Achar, P. S. Sastry
Discovering frequent chain episodes. Knowl. Inf. Syst. 60 (1) (2019)
Kulin Shah, P. S. Sastry, Naresh Manwani
PLUME: Polyhedral Learning Using Mixture of Experts. CoRR (2019)
Vidyadhar Upadhya, P. S. Sastry
Efficient Learning of Restricted Boltzmann Machines Using Covariance Estimates. ACML (2019)
Vidyadhar Upadhya, P. S. Sastry
Efficient Learning of Restricted Boltzmann Machines Using Covariance estimates. CoRR (2018)
Suresh Kirthi Kumaraswamy, P. S. Sastry, K. R. Ramakrishnan
Multi-source Subnetwork-level Transfer in CNNs Using Filter-Trees. IJCNN (2018)
Himanshu Kumar, P. S. Sastry
Robust Loss Functions for Learning Multi-class Classifiers. SMC (2018)
Vidyadhar Upadhya, P. S. Sastry
Learning RBM with a DC programming Approach. CoRR (2017)
Aritra Ghosh, Himanshu Kumar, P. S. Sastry
Robust Loss Functions under Label Noise for Deep Neural Networks. AAAI (2017)
Suresh Kirthi Kumaraswamy, P. S. Sastry, K. R. Ramakrishnan
Transfer Learning in CNNs Using Filter-Trees. CoRR (2017)
Aritra Ghosh, Naresh Manwani, P. S. Sastry
On the Robustness of Decision Tree Learning Under Label Noise. PAKDD (1) (2017)
Aritra Ghosh, Himanshu Kumar, P. S. Sastry
Robust Loss Functions under Label Noise for Deep Neural Networks. CoRR (2017)
Vidyadhar Upadhya, P. S. Sastry
Learning RBM with a DC programming Approach. ACML (2017)
A. Ibrahim, Shivakumar Sastry, P. S. Sastry
Discovering compressing serial episodes from event sequences. Knowl. Inf. Syst. 47 (2) (2016)
A. Ibrahim, P. S. Sastry, Shivakumar Sastry
Analyzing Similarities of Datasets Using a Pattern Set Kernel. PAKDD (1) (2016)
Aritra Ghosh, Naresh Manwani, P. S. Sastry
On the Robustness of Decision Tree Learning under Label Noise. CoRR (2016)
Suresh Kirthi Kumaraswamy, P. S. Sastry, Kalpathi Ramakrishnan
Bank of Weight Filters for Deep CNNs. ACML (2016)
Vidyadhar Upadhya, P. S. Sastry
Empirical Analysis of Sampling Based Estimators for Evaluating RBMs. CoRR (2015)
A. Ibrahim, P. S. Sastry, Shivakumar Sastry
Pattern set kernel. CODS (2015)
Naresh Manwani, P. S. Sastry
K-plane regression. Inf. Sci. 292 (2015)
Avinash Achar, P. S. Sastry
Statistical significance of episodes with general partial orders. Inf. Sci. 296 (2015)
Aritra Ghosh, Naresh Manwani, P. S. Sastry
Making risk minimization tolerant to label noise. Neurocomputing 160 (2015)
Vidyadhar Upadhya, P. S. Sastry
Empirical Analysis of Sampling Based Estimators for Evaluating RBMs. ICONIP (2) (2015)
Aritra Ghosh, Naresh Manwani, P. S. Sastry
Making Risk Minimization Tolerant to Label Noise. CoRR (2014)
A. Ibrahim, Shivakumar Sastry, P. S. Sastry
Discovering Compressing Serial Episodes from Event Sequences. CoRR (2014)
Avinash Achar, A. Ibrahim, P. S. Sastry
Pattern-growth based frequent serial episode discovery. Data Knowl. Eng. 87 (2013)
Shivakumar Sastry, Michael S. Branicky, P. S. Sastry
Cloud Conveyors System: A Versatile Application for Exploring Cyber-Physical Systems. CPSW@CISS (2013)
Naresh Manwani, P. S. Sastry
Noise Tolerance Under Risk Minimization. IEEE Trans. Cybern. 43 (3) (2013)
Avinash Achar, Srivatsan Laxman, Raajay Viswanathan, P. S. Sastry
Discovering injective episodes with general partial orders. Data Min. Knowl. Discov. 25 (1) (2012)
Naresh Manwani, P. S. Sastry
Geometric Decision Tree. IEEE Trans. Syst. Man Cybern. Part B 42 (1) (2012)
Naresh Manwani, P. S. Sastry
K-Plane Regression CoRR (2012)
Avinash Achar, Srivatsan Laxman, P. S. Sastry
A unified view of the apriori-based algorithms for frequent episode discovery. Knowl. Inf. Syst. 31 (2) (2012)
Naresh Manwani, P. S. Sastry
Polyceptron: A Polyhedral Learning Algorithm CoRR (2011)
Naresh Manwani, P. S. Sastry
Noise Tolerance under Risk Minimization CoRR (2011)
P. S. Sastry, K. P. Unnikrishnan
Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains. Neural Comput. 22 (4) (2010)
P. S. Sastry, G. D. Nagendra, Naresh Manwani
A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces. IEEE Trans. Syst. Man Cybern. Part B 40 (1) (2010)
Avinash Achar, Srivatsan Laxman, P. S. Sastry
A unified view of Automata-based algorithms for Frequent Episode Discovery CoRR (2010)
Raajay Viswanathan, P. S. Sastry, K. P. Unnikrishnan
Efficient Discovery of Large Synchronous Events in Neural Spike Streams CoRR (2010)
Naresh Manwani, P. S. Sastry
Learning Polyhedral Classifiers Using Logistic Function. ACML (2010)
Srivatsan Laxman, Basel Shadid, P. S. Sastry, K. P. Unnikrishnan
Temporal data mining for root-cause analysis of machine faults in automotive assembly lines CoRR (2009)
Kranthi K. Mamidisetty, Minlan Duan, Shivakumar Sastry, P. S. Sastry
Multipath Dissemination in Regular Mesh Topologies. IEEE Trans. Parallel Distributed Syst. 20 (8) (2009)
Avinash Achar, Srivatsan Laxman, V. Raajay, P. S. Sastry
Discovering general partial orders in event streams CoRR (2009)
Casey Diekman, Kohinoor Dasgupta, Vijay N. Nair, P. S. Sastry, K. P. Unnikrishnan
Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes. CoRR (2009)
Naresh Manwani, P. S. Sastry
A Geometric Algorithm for Learning Oblique Decision Trees. PReMI (2009)
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan
Inferring Neuronal Network Connectivity from Spike Data: A Temporal Datamining Approach CoRR (2008)
P. S. Sastry, K. P. Unnikrishnan
Conditional probability based significance tests for sequential patterns in multi-neuronal spike trains CoRR (2008)
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan
Inferring neuronal network connectivity from spike data: A temporal data mining approach. Sci. Program. 16 (1) (2008)
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan
Inferring Neuronal Network Connectivity using Time-constrained Episodes CoRR (2007)
K. P. Unnikrishnan, Debprakash Patnaik, P. S. Sastry
Discovering Patterns in Multi-neuronal Spike Trains using the Frequent Episode Method CoRR (2007)
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
Discovering Frequent Generalized Episodes When Events Persist for Different Durations. IEEE Trans. Knowl. Data Eng. 19 (9) (2007)
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
A fast algorithm for finding frequent episodes in event streams. KDD (2007)
Shesha Shah, P. S. Sastry
A Feedback-Based Algorithm for Motion Analysis with Application to Object Tracking. EURASIP J. Adv. Signal Process. 2007 (2007)
K. P. Unnikrishnan, Naren Ramakrishnan, P. S. Sastry, Ramasamy Uthurusamy
Network reconstruction from dynamic data. SIGKDD Explor. 8 (2) (2006)
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
Discovering Frequent Episodes and Learning Hidden Markov Models: A Formal Connection. IEEE Trans. Knowl. Data Eng. 17 (11) (2005)
P. S. Sastry, M. Magesh, K. P. Unnikrishnan
Two Timescale Analysis of the Alopex Algorithm for Optimization. Neural Comput. 14 (11) (2002)
G. Santharam, P. S. Sastry
A reinforcement learning neural network for adaptive control of Markov chains. IEEE Trans. Syst. Man Cybern. Part A 27 (5) (1997)
Kanagasabai Rajaraman, P. S. Sastry
Finite time analysis of the pursuit algorithm for learning automata. IEEE Trans. Syst. Man Cybern. Part B 26 (4) (1996)
P. S. Sastry, G. Santharam, K. P. Unnikrishnan
Memory neuron networks for identification and control of dynamical systems. IEEE Trans. Neural Networks 5 (2) (1994)
P. S. Sastry, Kanagasabai Rajaraman, S. R. Ranjan
Learning optimal conjunctive concepts through a team of stochastic automata. IEEE Trans. Syst. Man Cybern. 23 (4) (1993)
Subhashis Banerjee, P. S. Sastry, Y. V. Venkatesh
Surface reconstruction from disparate shading: an integration of shape-from-shading and stereopsis. ICPR (1) (1992)
K. Ravikanth, P. S. Sastry, Y. V. Venkatesh
Simulation studies on the performance of an organizational model for graph reduction. Future Gener. Comput. Syst. 6 (2) (1990)
K. Banerjee, P. S. Sastry, K. R. Ramakrishnan, Y. V. Venkatesh
An SIMD machine for low-level vision. Inf. Sci. 44 (1) (1988)
K. Ravikanth, P. S. Sastry, K. R. Ramakrishnan, Y. V. Venkatesh
A reduction architecture for the optimal scheduling of binary trees. Future Gener. Comput. Syst. 4 (3) (1988)