Follow
Mohit Sewak
Mohit Sewak
Microsoft R&D
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Practical convolutional neural networks: implement advanced deep learning models using Python
M Sewak, MR Karim, P Pujari
Packt Publishing Ltd, 2018
1532018
Deep reinforcement learning
M Sewak
Springer Singapore, 2019
1132019
Malware Detection Using Machine Learning and Deep Learning
H Rathore, S Agarwal, SK Sahay, M Sewak
952019
Comparison of deep learning and the classical machine learning algorithm for the malware detection
M Sewak, SK Sahay, H Rathore
2018 19th IEEE/ACIS international conference on software engineering …, 2018
712018
Deep Q Network (DQN), Double DQN, and Dueling DQN: A Step Towards General Artificial Intelligence
M Sewak, M Sewak
Deep Reinforcement Learning: Frontiers of Artificial Intelligence, 95-108, 2019
432019
An investigation of a deep learning based malware detection system
M Sewak, SK Sahay, H Rathore
Proceedings of the 13th International Conference on Availability …, 2018
432018
Robust android malware detection system against adversarial attacks using q-learning
H Rathore, SK Sahay, P Nikam, M Sewak
Information Systems Frontiers 23, 867-882, 2021
402021
An overview of deep learning architecture of deep neural networks and autoencoders
M Sewak, SK Sahay, H Rathore
Journal of Computational and Theoretical Nanoscience 17 (1), 182-188, 2020
402020
Winning in the Era of Serverless Computing and Function as a Service
M Sewak, S Singh
2018 3rd International Conference for Convergence in Technology (I2CT), 1-5, 2018
402018
IoT and distributed machine learning powered optimal state recommender solution
M Sewak, S Singh
2016 International Conference on Internet of Things and Applications (IOTA …, 2016
202016
Identification of significant permissions for efficient android malware detection
H Rathore, SK Sahay, R Rajvanshi, M Sewak
Broadband Communications, Networks, and Systems: 11th EAI International …, 2021
172021
Android Malicious Application Classification Using Clustering
H Rathore, SK Sahay, P Chaturvedi, M Sewak
162019
DOOM: A Novel Adversarial-DRL-Based Op-Code Level Metamorphic Malware Obfuscator for the Enhancement of IDS
M Sewak, SK Sahay, H Rathore
Proceedings of the 2020 ACM International Joint Conference on Pervasive and …, 2020
152020
Detection of malicious android applications: Classical machine learning vs. deep neural network integrated with clustering
H Rathore, SK Sahay, S Thukral, M Sewak
Broadband Communications, Networks, and Systems: 11th EAI International …, 2021
132021
Predicting customer value
YJ Chu, M Sewak, JY Shyr
US Patent App. 14/281,277, 2015
132015
DeepIntent: ImplicitIntent based Android IDS with E2E Deep Learning architecture
M Sewak, SK Sahay, H Rathore
2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile …, 2020
122020
Policy-Based Reinforcement Learning Approaches: Stochastic Policy Gradient and the REINFORCE Algorithm
M Sewak, M Sewak
Deep Reinforcement Learning: Frontiers of Artificial Intelligence, 127-140, 2019
102019
Trend-factored RFM scores to improve campaign performance
M Sewak
US Patent 10,152,726, 2018
92018
IBM predictive maintenance and quality 2.0 technical overview
V Negandhi, L Sreenivasan, R Giffen, M Sewak, A Rajasekharan
IBM Redbooks, 2015
92015
DRLDO: A Novel DRL based De obfuscation System for Defense Against Metamorphic Malware
M Sewak, SK Sahay, H Rathore
Defence Science Journal 71 (1), 55-65, 2021
82021
The system can't perform the operation now. Try again later.
Articles 1–20