no code implementations • 17 Apr 2024 • Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini
However, structure-based architectures such as Graph Neural Networks (GNNs) are yet to show the benefits of scale mainly due to the lower efficiency of sparse operations, large data requirements, and lack of clarity about the effectiveness of various architectures.
no code implementations • 29 Sep 2021 • Karush Suri
Multi-Agent Reinforcement Learning (MARL) has demonstrated significant success by virtue of collaboration across agents.
no code implementations • 29 Sep 2021 • Karush Suri, Florian Shkurti
The proposed answer studies conservatism in light of value function optimization, approximate objectives that upper bound underestimations and behavior cloning as auxilary regularization objective.
no code implementations • 16 Feb 2021 • Karush Suri, Xiao Qi Shi, Konstantinos Plataniotis, Yuri Lawryshyn
We present Trade Execution using Reinforcement Learning (TradeR) which aims to address two such practical challenges of catastrophy and surprise minimization by formulating trading as a real-world hierarchical RL problem.
Hierarchical Reinforcement Learning reinforcement-learning +1
1 code implementation • 16 Sep 2020 • Karush Suri, Xiao Qi Shi, Konstantinos Plataniotis, Yuri Lawryshyn
(2) EMIX highlights a practical use of energy functions in MARL with theoretical guarantees and experiment validations of the energy operator.
2 code implementations • 24 Jul 2020 • Karush Suri, Xiao Qi Shi, Konstantinos N. Plataniotis, Yuri A. Lawryshyn
Advances in Reinforcement Learning (RL) have demonstrated data efficiency and optimal control over large state spaces at the cost of scalable performance.
no code implementations • 27 Apr 2020 • Karush Suri, Rinki Gupta
Sign Language is used by the deaf community all over world.
no code implementations • 27 Apr 2020 • Karush Suri, Rinki Gupta
The predicted outputs are analyzed in the form of classification accuracies which are then compared to the conventional classification schemes of SVM and kNN.
no code implementations • 27 Apr 2020 • Karush Suri, Rinki Gupta
Recent advancements in diagnostic learning and development of gesture-based human machine interfaces have driven surface electromyography (sEMG) towards significant importance.
no code implementations • 27 Apr 2020 • Karush Suri, Rinki Gupta
The performance of the proposed approach is compared to the conventional single stage classification approach in terms of classification accuracies.
no code implementations • 27 Apr 2020 • Rinki Gupta, Karush Suri
Classified outputs are compared with the transition regions in a stimulus given to the subject to perform the activity.
no code implementations • 21 Apr 2020 • Karush Suri, Rinki Gupta
The proposed work presents a novel one-dimensional Convolutional Neural Network (CNN) array architecture for recognition of signs from the Indian sign language using signals recorded from a custom designed wearable IMU device.