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ORCIDP. S. Sastry 0001
Person information
- affiliation: Indian Institute of Science, Dept. of Computer Science and Automation, Bangalore, India
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Journal Articles
- 2022
[j39]Vidyadhar Upadhya
, P. S. Sastry:
Learning Gaussian-Bernoulli RBMs Using Difference of Convex Functions Optimization. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5728-5738 (2022)- 2020
- [j38]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: 2 (2020) - 2019
- [j37]Avinash Achar, P. S. Sastry:
Discovering frequent chain episodes. Knowl. Inf. Syst. 60(1): 447-494 (2019) - 2016
- [j36]A. Ibrahim, Shivakumar Sastry, P. S. Sastry:
Discovering compressing serial episodes from event sequences. Knowl. Inf. Syst. 47(2): 405-432 (2016) - 2015
- [j35]Aritra Ghosh, Naresh Manwani, P. S. Sastry:
Making risk minimization tolerant to label noise. Neurocomputing 160: 93-107 (2015) - [j34]Naresh Manwani, P. S. Sastry:
K-plane regression. Inf. Sci. 292: 39-56 (2015) - [j33]Avinash Achar, P. S. Sastry:
Statistical significance of episodes with general partial orders. Inf. Sci. 296: 175-200 (2015) - 2013
- [j32]Avinash Achar, A. Ibrahim, P. S. Sastry:
Pattern-growth based frequent serial episode discovery. Data Knowl. Eng. 87: 91-108 (2013) - [j31]Naresh Manwani, P. S. Sastry:
Noise Tolerance Under Risk Minimization. IEEE Trans. Cybern. 43(3): 1146-1151 (2013) - 2012
- [j30]Avinash Achar, Srivatsan Laxman, Raajay Viswanathan, P. S. Sastry:
Discovering injective episodes with general partial orders. Data Min. Knowl. Discov. 25(1): 67-108 (2012) - [j29]Avinash Achar, Srivatsan Laxman, P. S. Sastry:
A unified view of the apriori-based algorithms for frequent episode discovery. Knowl. Inf. Syst. 31(2): 223-250 (2012) - [j28]Naresh Manwani, P. S. Sastry:
Geometric Decision Tree. IEEE Trans. Syst. Man Cybern. Part B 42(1): 181-192 (2012) - 2010
- [j27]P. S. Sastry, K. P. Unnikrishnan:
Conditional Probability-Based Significance Tests for Sequential Patterns in Multineuronal Spike Trains. Neural Comput. 22(4): 1025-1059 (2010) - [j26]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): 19-28 (2010) - 2009
- [j25]Kranthi K. Mamidisetty, Minlan Duan, Shivakumar Sastry, P. S. Sastry:
Multipath Dissemination in Regular Mesh Topologies. IEEE Trans. Parallel Distributed Syst. 20(8): 1188-1201 (2009) - 2008
- [j24]Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan:
Inferring neuronal network connectivity from spike data: A temporal data mining approach. Sci. Program. 16(1): 49-77 (2008) - 2007
- [j23]Shesha Shah, P. S. Sastry:
A Feedback-Based Algorithm for Motion Analysis with Application to Object Tracking. EURASIP J. Adv. Signal Process. 2007 (2007) - [j22]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): 1188-1201 (2007) - 2006
- [j21]K. P. Unnikrishnan, Naren Ramakrishnan, P. S. Sastry, Ramasamy Uthurusamy:
Network reconstruction from dynamic data. SIGKDD Explor. 8(2): 90-91 (2006) - 2005
- [j20]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): 1505-1517 (2005) - 2004
- [j19]Shesha Shah, P. S. Sastry:
Fingerprint classification using a feedback-based line detector. IEEE Trans. Syst. Man Cybern. Part B 34(1): 85-94 (2004) - 2002
- [j18]P. S. Sastry, M. Magesh, K. P. Unnikrishnan:
Two Timescale Analysis of the Alopex Algorithm for Optimization. Neural Comput. 14(11): 2729-2750 (2002) - [j17]M. A. L. Thathachar, P. S. Sastry:
Varieties of learning automata: an overview. IEEE Trans. Syst. Man Cybern. Part B 32(6): 711-722 (2002) - 1999
- [j16]Shesha Shah, P. S. Sastry:
New algorithms for learning and pruning oblique decision trees. IEEE Trans. Syst. Man Cybern. Part C 29(4): 494-505 (1999) - [j15]K. Rajaraman, P. S. Sastry:
Stochastic optimization over continuous and discrete variables with applications to concept learning under noise. IEEE Trans. Syst. Man Cybern. Part A 29(6): 542-553 (1999) - 1997
- [j14]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): 588-600 (1997) - 1996
- [j13]Kanagasabai Rajaraman, P. S. Sastry:
Finite time analysis of the pursuit algorithm for learning automata. IEEE Trans. Syst. Man Cybern. Part B 26(4): 590-598 (1996) - 1994
- [j12]P. S. Sastry, M. A. L. Thathachar:
Analysis of Stochastic Automata Algorithm for Relaxation Labeling. IEEE Trans. Pattern Anal. Mach. Intell. 16(5): 538-543 (1994) - [j11]P. S. Sastry, G. Santharam, K. P. Unnikrishnan:
Memory neuron networks for identification and control of dynamical systems. IEEE Trans. Neural Networks 5(2): 306-319 (1994) - [j10]Vijay V. Phansalkar, P. S. Sastry:
Analysis of the back-propagation algorithm with momentum. IEEE Trans. Neural Networks 5(3): 505-506 (1994) - [j9]P. S. Sastry, Vijay V. Phansalkar, M. A. L. Thathachar:
Decentralized Learning of Nash Equilibria in Multi-Person Stochastic Games With Incomplete Information. IEEE Trans. Syst. Man Cybern. Syst. 24(5): 769-777 (1994) - 1993
- [j8]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): 1175-1184 (1993) - 1990
- [j7]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): 163-180 (1990) - 1988
- [j6]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): 225-233 (1988) - [j5]K. Banerjee, P. S. Sastry, K. R. Ramakrishnan, Y. V. Venkatesh:
An SIMD machine for low-level vision. Inf. Sci. 44(1): 19-50 (1988) - 1987
- [j4]M. A. L. Thathachar, P. S. Sastry:
A hierarchical system of learning automata that can learn die globally optimal path. Inf. Sci. 42(2): 143-166 (1987) - [j3]Mandayam A. L. Thathachar, P. S. Sastry:
Learning Optimal Discriminant Functions through a Cooperative Game of Automata. IEEE Trans. Syst. Man Cybern. 17(1): 73-85 (1987) - 1986
- [j2]Mandayam A. L. Thathachar, P. S. Sastry:
Relaxation Labeling with Learning Automata. IEEE Trans. Pattern Anal. Mach. Intell. 8(2): 256-268 (1986) - 1985
- [j1]M. A. L. Thathachar, P. S. Sastry:
A new approach to the design of reinforcement schemes for learning automata. IEEE Trans. Syst. Man Cybern. 15(1): 168-175 (1985)
Conference and Workshop Papers
- 2024
- [c20]Santhosh B. Gandreti, Ibrahim A., P. S. Sastry:
Breadth-First Search Approach for Mining Serial Episodes with Simultaneous Events. COMAD/CODS 2024: 36-44 - 2023
- [c19]Santhosh B. Gandreti, P. S. Sastry:
Efficient Depth-First Search Approach for Mining Injective General Episodes. COMAD/CODS 2023: 1-9 - [c18]Deep Patel, P. S. Sastry:
Adaptive Sample Selection for Robust Learning under Label Noise. WACV 2023: 3921-3931 - 2021
- [c17]Deep Patel, P. S. Sastry:
Memorization in Deep Neural Networks: Does the Loss Function Matter? PAKDD (2) 2021: 131-142 - 2020
- [c16]Himanshu Kumar, Naresh Manwani, P. S. Sastry:
Robust Learning of Multi-Label Classifiers under Label Noise. COMAD/CODS 2020: 90-97 - 2019
- [c15]Vidyadhar Upadhya, P. S. Sastry:
Efficient Learning of Restricted Boltzmann Machines Using Covariance Estimates. ACML 2019: 836-851 - 2018
- [c14]Suresh Kirthi Kumaraswamy, P. S. Sastry, K. R. Ramakrishnan:
Multi-source Subnetwork-level Transfer in CNNs Using Filter-Trees. IJCNN 2018: 1-8 - [c13]Himanshu Kumar, P. S. Sastry:
Robust Loss Functions for Learning Multi-class Classifiers. SMC 2018: 687-692 - 2017
- [c12]Aritra Ghosh, Himanshu Kumar, P. S. Sastry:
Robust Loss Functions under Label Noise for Deep Neural Networks. AAAI 2017: 1919-1925 - [c11]Vidyadhar Upadhya, P. S. Sastry:
Learning RBM with a DC programming Approach. ACML 2017: 498-513 - [c10]Aritra Ghosh, Naresh Manwani, P. S. Sastry:
On the Robustness of Decision Tree Learning Under Label Noise. PAKDD (1) 2017: 685-697 - 2016
- [c9]Suresh Kirthi Kumaraswamy, P. S. Sastry, Kalpathi Ramakrishnan:
Bank of Weight Filters for Deep CNNs. ACML 2016: 334-349 - [c8]A. Ibrahim, P. S. Sastry, Shivakumar Sastry:
Analyzing Similarities of Datasets Using a Pattern Set Kernel. PAKDD (1) 2016: 265-276 - 2015
- [c7]A. Ibrahim, P. S. Sastry, Shivakumar Sastry:
Pattern set kernel. CODS 2015: 122-123 - [c6]Vidyadhar Upadhya, P. S. Sastry:
Empirical Analysis of Sampling Based Estimators for Evaluating RBMs. ICONIP (2) 2015: 545-553 - 2013
- [c5]Shivakumar Sastry, Michael S. Branicky, P. S. Sastry:
Cloud Conveyors System: A Versatile Application for Exploring Cyber-Physical Systems. CPSW@CISS 2013: 43-62 - 2010
- [c4]Naresh Manwani, P. S. Sastry:
Learning Polyhedral Classifiers Using Logistic Function. ACML 2010: 17-30 - 2009
- [c3]Naresh Manwani, P. S. Sastry:
A Geometric Algorithm for Learning Oblique Decision Trees. PReMI 2009: 25-31 - 2007
- [c2]Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan:
A fast algorithm for finding frequent episodes in event streams. KDD 2007: 410-419 - 1992
- [c1]Subhashis Banerjee, P. S. Sastry, Y. V. Venkatesh:
Surface reconstruction from disparate shading: an integration of shape-from-shading and stereopsis. ICPR (1) 1992: 141-144
Editorship
- 2009
- [e1]Santanu Chaudhury, Sushmita Mitra, C. A. Murthy, P. S. Sastry, Sankar K. Pal:
Pattern Recognition and Machine Intelligence, Third International Conference, PReMI 2009, New Delhi, India, December 16-20, 2009 Proceedings. Lecture Notes in Computer Science 5909, Springer 2009, ISBN 978-3-642-11163-1 [contents]
Informal and Other Publications
- 2021
- [i25]Vidyadhar Upadhya, P. S. Sastry:
Learning Gaussian-Bernoulli RBMs using Difference of Convex Functions Optimization. CoRR abs/2102.06228 (2021) - [i24]Deep Patel, P. S. Sastry:
Adaptive Sample Selection for Robust Learning under Label Noise. CoRR abs/2106.15292 (2021) - [i23]Deep Patel, P. S. Sastry:
Memorization in Deep Neural Networks: Does the Loss Function matter? CoRR abs/2107.09957 (2021) - 2019
- [i22]Soumyajit Mitra, P. S. Sastry:
Summarizing Event Sequences with Serial Episodes: A Statistical Model and an Application. CoRR abs/1904.00516 (2019) - [i21]Kulin Shah, P. S. Sastry, Naresh Manwani:
PLUME: Polyhedral Learning Using Mixture of Experts. CoRR abs/1904.09948 (2019) - 2018
- [i20]Vidyadhar Upadhya, P. S. Sastry:
Efficient Learning of Restricted Boltzmann Machines Using Covariance estimates. CoRR abs/1810.10777 (2018) - 2017
- [i19]Vidyadhar Upadhya, P. S. Sastry:
Learning RBM with a DC programming Approach. CoRR abs/1709.07149 (2017) - [i18]Suresh Kirthi Kumaraswamy, P. S. Sastry, K. R. Ramakrishnan:
Transfer Learning in CNNs Using Filter-Trees. CoRR abs/1711.09648 (2017) - [i17]Aritra Ghosh, Himanshu Kumar, P. S. Sastry:
Robust Loss Functions under Label Noise for Deep Neural Networks. CoRR abs/1712.09482 (2017) - 2016
- [i16]Aritra Ghosh, Naresh Manwani, P. S. Sastry:
On the Robustness of Decision Tree Learning under Label Noise. CoRR abs/1605.06296 (2016) - 2015
- [i15]Vidyadhar Upadhya, P. S. Sastry:
Empirical Analysis of Sampling Based Estimators for Evaluating RBMs. CoRR abs/1510.02255 (2015) - 2014
- [i14]A. Ibrahim, Shivakumar Sastry, P. S. Sastry:
Discovering Compressing Serial Episodes from Event Sequences. CoRR abs/1401.1043 (2014) - [i13]Aritra Ghosh, Naresh Manwani, P. S. Sastry:
Making Risk Minimization Tolerant to Label Noise. CoRR abs/1403.3610 (2014) - 2012
- [i12]Naresh Manwani, P. S. Sastry:
K-Plane Regression. CoRR abs/1211.1513 (2012) - 2011
- [i11]Naresh Manwani, P. S. Sastry:
Polyceptron: A Polyhedral Learning Algorithm. CoRR abs/1107.1564 (2011) - [i10]Naresh Manwani, P. S. Sastry:
Noise Tolerance under Risk Minimization. CoRR abs/1109.5231 (2011) - 2010
- [i9]Raajay Viswanathan, P. S. Sastry, K. P. Unnikrishnan:
Efficient Discovery of Large Synchronous Events in Neural Spike Streams. CoRR abs/1006.1543 (2010) - [i8]Avinash Achar, Srivatsan Laxman, P. S. Sastry:
A unified view of Automata-based algorithms for Frequent Episode Discovery. CoRR abs/1007.0690 (2010) - 2009
- [i7]Avinash Achar, Srivatsan Laxman, V. Raajay, P. S. Sastry:
Discovering general partial orders in event streams. CoRR abs/0902.1227 (2009) - [i6]Casey O. Diekman, Kohinoor Dasgupta, Vijay N. Nair, P. S. Sastry, K. P. Unnikrishnan:
Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes. CoRR abs/0902.3725 (2009) - [i5]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 abs/0904.4608 (2009) - 2008
- [i4]Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan:
Inferring Neuronal Network Connectivity from Spike Data: A Temporal Datamining Approach. CoRR abs/0803.0450 (2008) - [i3]P. S. Sastry, K. P. Unnikrishnan:
Conditional probability based significance tests for sequential patterns in multi-neuronal spike trains. CoRR abs/0808.3511 (2008) - 2007
- [i2]Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishnan:
Inferring Neuronal Network Connectivity using Time-constrained Episodes. CoRR abs/0709.0218 (2007) - [i1]K. P. Unnikrishnan, Debprakash Patnaik, P. S. Sastry:
Discovering Patterns in Multi-neuronal Spike Trains using the Frequent Episode Method. CoRR abs/0709.0566 (2007)
Coauthor Index
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