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2010 – today
- 2018
[c23]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- [i9]S. Saikia, R. Verma, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, A. Srinivasan:
Evolutionary RL for Container Loading. CoRR abs/1805.06664 (2018) - 2017
- [j9]Kushal Veer Singh, Lovekesh Vig:
Improved prediction of missing protein interactome links via anomaly detection. Applied Network Science 2: 2 (2017) - [c22]Prerna Khurana, Puneet Agarwal, Gautam Shroff, Lovekesh Vig, Ashwin Srinivasan:
Hybrid BiLSTM-Siamese network for FAQ Assistance. CIKM 2017: 537-545 - [c21]Monika Sharma, Oindrila Saha, Anand Sriraman, Ramya Hebbalaguppe, Lovekesh Vig, Shirish Karande:
Crowdsourcing for Chromosome Segmentation and Deep Classification. CVPR Workshops 2017: 786-793 - [c20]Mohit Yadav, Lovekesh Vig, Gautam Shroff:
Learning and Knowledge Transfer with Memory Networks for Machine Comprehension. EACL (1) 2017: 850-859 - [c19]Swati, Gaurav Gupta, Mohit Yadav, Monika Sharma, Lovekesh Vig:
Siamese Networks for Chromosome Classification. ICCV Workshops 2017: 72-81 - [c18]Somdyuti Paul, Lovekesh Vig:
Deterministic Policy Gradient Based Robotic Path Planning with Continuous Action Spaces. ICCV Workshops 2017: 725-733 - [c17]Gaurav Gupta, Swati, Monika Sharma, Lovekesh Vig:
Information Extraction from Hand-Marked Industrial Inspection Sheets. CBDAR@ICDAR 2017: 33-38 - [c16]S. Vishal, Mohit Yadav, Lovekesh Vig, Gautam Shroff:
Information Bottleneck Inspired Method For Chat Text Segmentation. IJCNLP(1) 2017: 194-203 - [c15]Lovekesh Vig, Ashwin Srinivasan, Michael Bain, Ankit Verma:
An Investigation into the Role of Domain-Knowledge on the Use of Embeddings. ILP 2017: 169-183 - [c14]Monika Sharma, Ramya Hebbalaguppe, Lovekesh Vig:
Pre-trained classifiers with One Shot Similarity for context aware face verification and identification. ISBA 2017: 1-7 - [i8]Karamjit Singh, Garima Gupta, Lovekesh Vig, Gautam Shroff, Puneet Agarwal:
Deep Convolutional Neural Networks for Pairwise Causality. CoRR abs/1701.00597 (2017) - [i7]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) - [i6]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
- [c13]Ankit Verma, Monika Sharma, Ramya Hebbalaguppe, Ehtesham Hassan, Lovekesh Vig:
Automatic Container Code Recognition via Spatial Transformer Networks and Connected Component Region Proposals. ICMLA 2016: 728-733 - [c12]Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia:
Generation of Near-Optimal Solutions Using ILP-Guided Sampling. ILP 2016: 120-131 - [c11]Ramakrishna Perla, Ehtesham Hassan, Ramya Hebbalaguppe, Monika Sharma, Gaurav Gupta, Lovekesh Vig, Geetika Sharma, Gautam Shroff:
An AR Inspection Framework: Feasibility Study with Multiple AR Devices. ISMAR Adjunct 2016: 221-226 - [c10]Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat:
Neuro-Symbolic EDA-Based Optimization Using ILP-Enhanced DBNs. CoCo@NIPS 2016 - [i5]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) - [i4]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) - [i3]Ashwin Srinivasan, Gautam Shroff, Lovekesh Vig, Sarmimala Saikia, Puneet Agarwal:
Generation of Near-Optimal Solutions Using ILP-Guided Sampling. CoRR abs/1608.01093 (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) - [i1]Sarmimala Saikia, Lovekesh Vig, Ashwin Srinivasan, Gautam Shroff, Puneet Agarwal, Richa Rawat:
Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs. CoRR abs/1612.06528 (2016) - 2015
- [j8]Manoj Agarwal, Nitin Agrawal, Shikhar Sharma, Lovekesh Vig, Naveen Kumar:
Parallel multi-objective multi-robot coalition formation. Expert Syst. Appl. 42(21): 7797-7811 (2015) - [c9]Sucheta Chauhan, Lovekesh Vig:
Anomaly detection in ECG time signals via deep long short-term memory networks. DSAA 2015: 1-7 - [c8]Urminder Singh, Sucheta Chauhan, A. Krishnamachari, Lovekesh Vig:
Ensemble of deep long short term memory networks for labelling origin of replication sequences. DSAA 2015: 1-7 - [c7]Ankit Verma, Ramya Hebbalaguppe, Lovekesh Vig, Swagat Kumar, Ehtesham Hassan:
Pedestrian Detection via Mixture of CNN Experts and Thresholded Aggregated Channel Features. ICCV Workshops 2015: 555-563 - 2014
- [j7]Manoj Agarwal, Naveen Kumar, Lovekesh Vig:
Non-additive multi-objective robot coalition formation. Expert Syst. Appl. 41(8): 3736-3747 (2014) - 2011
- [j6]Ashish Gupta, Lovekesh Vig, David C. Noelle:
A dual association model for the extinction of animal conditioning. Neurocomputing 74(17): 3531-3542 (2011) - [j5]Lovekesh Vig, Ashish Gupta, Abhinandan Basu:
A Neurocomputational Model for the Relation Between Hunger, Dopamine and Action Rate. J. Intelligent Systems 20(4): 373-393 (2011) - [j4]Manoj Agarwal, Lovekesh Vig, Naveen Kumar:
Multiple Objective Robot Coalition Formation. J. Intelligent Systems 20(4): 395-413 (2011) - [j3]Ashish Gupta, Lovekesh Vig, David C. Noelle:
A Cognitive Model for Generalization during Sequential Learning. J. Robotics 2011: 617613:1-617613:12 (2011) - [c6]Ashish Gupta, Lovekesh Vig:
A Dual Association Model for Acquisition and Extinction. AI*IA 2011: 139-150 - [c5]Manoj Agarwal, Lovekesh Vig, Naveen Kumar:
Multi-objective Robot Coalition Formation for Non-additive Environments. ICIRA (1) 2011: 346-355 - [c4]Manoj Agarwal, Lovekesh Vig, Naveen Kumar:
MORCFA: A Multiple Objective Robot Coalition Formation Algorithm. IICAI 2011: 268-279 - [c3]Lovekesh Vig, Ashish Gupta, Abhinandan Basu:
On the relation between hunger, dopamine and action rate. IICAI 2011: 1601-1617
2000 – 2009
- 2009
- [c2]Lovekesh Vig, Julie A. Adams:
The Effect of Coalition Imbalance on Multi-Robot Teams. IICAI 2009: 603-615 - 2007
- [j2]Lovekesh Vig, Julie A. Adams:
Coalition Formation: From Software Agents to Robots. Journal of Intelligent and Robotic Systems 50(1): 85-118 (2007) - 2006
- [j1]Lovekesh Vig, Julie A. Adams:
Multi-robot coalition formation. IEEE Trans. Robotics 22(4): 637-649 (2006) - 2005
- [c1]
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