Követés
Pankaj Malhotra
Pankaj Malhotra
Microsoft (prev. TCS Research)
E-mail megerősítve itt: microsoft.com
Cím
Hivatkozott rá
Hivatkozott rá
Év
Long Short Term Memory Networks for Anomaly Detection in Time Series
P Malhotra, L Vig, G Shroff, P Agarwal
23rd European Symposium on Artificial Neural Networks, Computational …, 2015
13252015
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection
P Malhotra, A Ramakrishnan, G Anand, L Vig, P Agarwal, G Shroff
Anomaly Detection Workshop at 33rd International Conference on Machine …, 2016
8582016
Multi-Sensor Prognostics using an Unsupervised Health Index based on LSTM Encoder-Decoder
P Malhotra, V TV, A Ramakrishnan, G Anand, L Vig, P Agarwal, G Shroff
1st ACM SIGKDD Workshop on Machine Learning for Prognostics and Health …, 2016
2192016
TimeNet: Pre-trained deep recurrent neural network for time series classification
P Malhotra, V TV, L Vig, P Agarwal, G Shroff
25th European Symposium on Artificial Neural Networks, Computational …, 2017
1512017
Predicting Remaining Useful Life Using Time Series Embeddings based on Recurrent Neural Networks
N Gugulothu, V TV, P Malhotra, L Vig, P Agarwal, G Shroff
International Journal of Prognostics and Health Management, 2018 9 (004), 2018
1462018
Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks
P Gupta, P Malhotra, L Vig, G Shroff
Machine Learning for Medicine and Healthcare Workshop at KDD 2018, 2018
81*2018
Sequence and Time Aware Neighborhood for Session-based Recommendations: STAN
D Garg, P Gupta, P Malhotra, L Vig, G Shroff
Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019
792019
Convtimenet: A pre-trained deep convolutional neural network for time series classification
K Kashiparekh, J Narwariya, P Malhotra, L Vig, G Shroff
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
652019
Online Anomaly Detection with Concept Drift Adaptation using Recurrent Neural Networks
S Saurav, P Malhotra, V TV, N Gugulothu, L Vig, P Agarwal, G Shroff
CoDS-COMAD '18 Proceedings of the ACM India Joint International Conference …, 2018
632018
Anomaly detection system and method
P Malhotra, G Shroff, P Agarwal, L Vig
US Patent 10,223,403, 2019
622019
NISER: Normalized item and session representations to handle popularity bias
P Gupta, D Garg, P Malhotra, L Vig, G Shroff
arXiv preprint arXiv:1909.04276, 2019
54*2019
Approximate Incremental Big-Data Harmonization
P Agarwal, G Shroff, P Malhotra
BigData Congress, 2013
412013
Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks
P Gupta, P Malhotra, J Narwariya, L Vig, G Shroff
402019
Graph-Parallel Entity Resolution using LSH & IMM
P Malhotra, P Agarwal, G Shroff
EDBT/ICDT Workshops, 2014
292014
Using Features from Pre-trained TimeNet for Clinical Predictions
P Gupta, P Malhotra, L Vig, G Shroff
3rd International Workshop on Knowledge Discovery in Healthcare Data at IJCAI, 2018
282018
Meta-learning for few-shot time series classification
J Narwariya, P Malhotra, L Vig, G Shroff, TV Vishnu
Proceedings of the 7th ACM IKDD CoDS and 25th COMAD, 28-36, 2020
262020
ODE-augmented Training Improves Anomaly Detection in Sensor Data from Machines
M Yadav, P Malhotra, L Vig, K Sriram, G Shroff
NIPS Time Series Workshop, 2015
252015
Graph neural networks for leveraging industrial equipment structure: An application to remaining useful life estimation
J Narwariya, P Malhotra, V TV, L Vig, G Shroff
arXiv preprint arXiv:2006.16556, 2020
192020
Data-driven prognostics with predictive uncertainty estimation using ensemble of deep ordinal regression models
TV Vishnu, P Malhotra, L Vig, G Shroff
International Journal of Prognostics and Health Management 10 (4), 2019
16*2019
Predicting remaining useful life using time series embeddings based on recurrent neural networks
VTV Narendhar Gugulothu, P Malhotra, L Vig, P Agarwal, G Shroff
arXiv preprint arXiv 1709, 63, 2017
152017
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Cikkek 1–20