Search Results for author: Avisek Naug

Found 10 papers, 1 papers with code

A Configurable Pythonic Data Center Model for Sustainable Cooling and ML Integration

no code implementations18 Apr 2024 Avisek Naug, Antonio Guillen, Ricardo Luna Gutierrez, Vineet Gundecha, Sahand Ghorbanpour, Sajad Mousavi, Ashwin Ramesh Babu, Soumyendu Sarkar

There have been growing discussions on estimating and subsequently reducing the operational carbon footprint of enterprise data centers.

Function Approximation for Reinforcement Learning Controller for Energy from Spread Waves

no code implementations17 Apr 2024 Soumyendu Sarkar, Vineet Gundecha, Sahand Ghorbanpour, Alexander Shmakov, Ashwin Ramesh Babu, Avisek Naug, Alexandre Pichard, Mathieu Cocho

Our results show that the transformer model of moderate depth with gated residual connections around the multi-head attention, multi-layer perceptron, and the transformer block (STrXL) proposed in this paper is optimal and boosts energy efficiency by an average of 22. 1% for these complex spread waves over the existing spring damper (SD) controller.

Multi-agent Reinforcement Learning reinforcement-learning

Sustainability of Data Center Digital Twins with Reinforcement Learning

1 code implementation16 Apr 2024 Soumyendu Sarkar, Avisek Naug, Antonio Guillen, Ricardo Luna, Vineet Gundecha, Ashwin Ramesh Babu, Sajad Mousavi

To tackle this, we've developed DCRL-Green, a multi-agent RL environment that empowers the ML community to design data centers and research, develop, and refine RL controllers for carbon footprint reduction in DCs.

reinforcement-learning Reinforcement Learning (RL)

Robustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning

no code implementations27 Mar 2024 Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi, Vineet Gundecha, Avisek Naug, Sahand Ghorbanpour

We present a generic Reinforcement Learning (RL) framework optimized for crafting adversarial attacks on different model types spanning from ECG signal analysis (1D), image classification (2D), and video classification (3D).

Classification Image Classification +2

Carbon Footprint Reduction for Sustainable Data Centers in Real-Time

no code implementations21 Mar 2024 Soumyendu Sarkar, Avisek Naug, Ricardo Luna, Antonio Guillen, Vineet Gundecha, Sahand Ghorbanpour, Sajad Mousavi, Dejan Markovikj, Ashwin Ramesh Babu

As machine learning workloads significantly increase energy consumption, sustainable data centers with low carbon emissions are becoming a top priority for governments and corporations worldwide.

Multi-agent Reinforcement Learning

RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels

no code implementations5 Oct 2023 Alexander Shmakov, Avisek Naug, Vineet Gundecha, Sahand Ghorbanpour, Ricardo Luna Gutierrez, Ashwin Ramesh Babu, Antonio Guillen, Soumyendu Sarkar

In this paper, we combine recent developments in Deep Kernel Learning (DKL) and attention-based Transformer models to improve the modeling powers of GP surrogates with meta-learning.

Bayesian Optimization Meta-Learning +2

PyDCM: Custom Data Center Models with Reinforcement Learning for Sustainability

no code implementations5 Oct 2023 Avisek Naug, Antonio Guillen, Ricardo Luna Gutiérrez, Vineet Gundecha, Dejan Markovikj, Lekhapriya Dheeraj Kashyap, Lorenz Krause, Sahand Ghorbanpour, Sajad Mousavi, Ashwin Ramesh Babu, Soumyendu Sarkar

The increasing global emphasis on sustainability and reducing carbon emissions is pushing governments and corporations to rethink their approach to data center design and operation.


A Relearning Approach to Reinforcement Learning for Control of Smart Buildings

no code implementations4 Aug 2020 Avisek Naug, Marcos Quiñones-Grueiro, Gautam Biswas

We demonstrate this approach for a data-driven 'smart building environment' that we use as a test-bed for developing HVAC controllers for reducing energy consumption of large buildings on our university campus.

reinforcement-learning Reinforcement Learning (RL)

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