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ORCIDPankaj Malhotra
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2020 – today
- 2024
[i22]Siddhant Kharbanda, Devaansh Gupta, Gururaj K, Pankaj Malhotra, Cho-Jui Hsieh, Rohit Babbar:
UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification. CoRR abs/2405.03714 (2024)- [i21]Bhawna Paliwal, Deepak Saini, Mudit Dhawan, Siddarth Asokan, Nagarajan Natarajan, Surbhi Aggarwal, Pankaj Malhotra, Jian Jiao, Manik Varma:
CROSS-JEM: Accurate and Efficient Cross-encoders for Short-text Ranking Tasks. CoRR abs/2409.09795 (2024) - 2022
- [i20]Jyoti Narwariya, Chetan Verma, Pankaj Malhotra, Lovekesh Vig, Easwar Subramanian, Sanjay Bhat:
Electricity Consumption Forecasting for Out-of-distribution Time-of-Use Tariffs. CoRR abs/2202.05517 (2022) - [i19]Diksha Garg, Pankaj Malhotra, Anil Bhatia, Sanjay Bhat, Lovekesh Vig, Gautam Shroff:
Learning to Liquidate Forex: Optimal Stopping via Adaptive Top-K Regression. CoRR abs/2202.12578 (2022) - [i18]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions. CoRR abs/2203.06852 (2022) - 2021
- [c18]Priyanka Gupta, Ankit Sharma, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
CauSeR: Causal Session-based Recommendations for Handling Popularity Bias. CIKM 2021: 3048-3052 - [c17]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions. ICDM 2021: 161-170 - [c16]Hritik Bansal, Gantavya Bhatt, Pankaj Malhotra, Prathosh AP:
Systematic Generalization in Neural Networks-based Multivariate Time Series Forecasting Models. IJCNN 2021: 1-8 - [c15]Asha Rajbhoj, Prateek Dhawan, Vishnu TV, Pankaj Malhotra, Vinay Kulkarni:
Re-Imagining data analytics software development. ISEC 2021: 20:1-20:5 - [i17]Hritik Bansal, Gantavya Bhatt, Pankaj Malhotra, Prathosh A. P.:
Systematic Generalization for Predictive Control in Multivariate Time Series. CoRR abs/2102.05602 (2021) - 2020
- [j1]Priyanka Gupta
, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis Using Deep Neural Networks. J. Heal. Informatics Res. 4(2): 112-137 (2020) - [c14]Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Vishnu TV:
Meta-Learning for Few-Shot Time Series Classification. COMAD/CODS 2020: 28-36 - [i16]Jyoti Narwariya, Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Gautam Shroff:
Graph Neural Networks for Leveraging Industrial Equipment Structure: An application to Remaining Useful Life Estimation. CoRR abs/2006.16556 (2020) - [i15]Vibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Handling Variable-Dimensional Time Series with Graph Neural Networks. CoRR abs/2007.00411 (2020) - [i14]Diksha Garg, Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation. CoRR abs/2012.08984 (2020)
2010 – 2019
- 2019
- [c13]Kaushal Paneri, Vishnu TV, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Regularizing Fully Convolutional Networks for Time Series Classification by Decorrelating Filters. AAAI 2019: 10003-10004 - [c12]Arijit Ukil, Pankaj Malhotra, Soma Bandyopadhyay, Tulika Bose, Ishan Sahu, Ayan Mukherjee, Lovekesh Vig, Arpan Pal, Gautam Shroff:
Fusing Features based on Signal Properties and TimeNet for Time Series Classification. ESANN 2019 - [c11]Kathan Kashiparekh, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification. IJCNN 2019: 1-8 - [c10]Vishnu TV, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Meta-Learning for Black-Box Optimization. ECML/PKDD (2) 2019: 366-381 - [c9]Diksha Garg, Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Sequence and Time Aware Neighborhood for Session-based Recommendations: STAN. SIGIR 2019: 1069-1072 - [i13]Vishnu TV, Diksha Garg, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models. CoRR abs/1903.09795 (2019) - [i12]Priyanka Gupta, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks. CoRR abs/1904.00655 (2019) - [i11]Kathan Kashiparekh, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification. CoRR abs/1904.12546 (2019) - [i10]Vishnu TV, Pankaj Malhotra, Jyoti Narwariya, Lovekesh Vig, Gautam Shroff:
Meta-Learning for Black-box Optimization. CoRR abs/1907.06901 (2019) - [i9]Priyanka Gupta, Diksha Garg, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
NISER: Normalized Item and Session Representations with Graph Neural Networks. CoRR abs/1909.04276 (2019) - [i8]Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Vishnu TV:
Meta-Learning for Few-Shot Time Series Classification. CoRR abs/1909.07155 (2019) - 2018
- [c8]Sakti Saurav, Pankaj Malhotra, Vishnu TV, Narendhar Gugulothu, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Online anomaly detection with concept drift adaptation using recurrent neural networks. COMAD/CODS 2018: 78-87 - [c7]Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Using Features From Pre-trained TimeNET For Clinical Predictions. KDH@IJCAI 2018: 38-44 - [i7]Priyanka Gupta, Pankaj Malhotra, Lovekesh Vig, Gautam Shroff:
Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks. CoRR abs/1807.01705 (2018) - 2017
- [c6]Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
TimeNet: Pre-trained deep recurrent neural network for time series classification. ESANN 2017 - [i6]Pankaj Malhotra, Vishnu TV, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
TimeNet: Pre-trained deep recurrent neural network for time series classification. CoRR abs/1706.08838 (2017) - [i5]Narendhar Gugulothu, Vishnu TV, Pankaj Malhotra, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks. CoRR abs/1709.01073 (2017) - 2016
- [i4]Mohit Yadav, Pankaj Malhotra, Lovekesh Vig, K. Sriram, Gautam Shroff:
ODE - Augmented Training Improves Anomaly Detection in Sensor Data from Machines. CoRR abs/1605.01534 (2016) - [i3]Pankaj Malhotra, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection. CoRR abs/1607.00148 (2016) - [i2]Pankaj Malhotra, Vishnu TV, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, Gautam Shroff:
Multi-Sensor Prognostics using an Unsupervised Health Index based on LSTM Encoder-Decoder. CoRR abs/1608.06154 (2016) - 2015
- [c5]Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
Long Short Term Memory Networks for Anomaly Detection in Time Series. ESANN 2015 - 2014
- [c4]Pankaj Malhotra, Puneet Agarwal, Gautam Shroff:
Graph-Parallel Entity Resolution using LSH & IMM. EDBT/ICDT Workshops 2014: 41-49 - [c3]Pankaj Malhotra, Puneet Agarwal, Gautam Shroff:
Incremental entity fusion from linked documents. FUSION 2014: 1-8 - [i1]Pankaj Malhotra, Puneet Agarwal, Gautam Shroff:
Incremental Entity Resolution from Linked Documents. CoRR abs/1402.4417 (2014) - 2013
- [c2]Puneet Agarwal, Gautam Shroff, Pankaj Malhotra:
Approximate Incremental Big-Data Harmonization. BigData Congress 2013: 118-125
2000 – 2009
- 2008
- [c1]Priyank Jindal, Pankaj Malhotra, V. Rihani, Sahil Rihani, Parkhi Sharma, Bhupendra Singh Chhabra:
A Neural Network For Prognosis of Chronic Myeloid Leukemia. IC-AI 2008: 263-268
Coauthor Index
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