Zobrazeno 1 - 10
of 295
pro vyhledávání: '"Ramakrishnan P. K."'
Federated Learning (FL) typically involves a large-scale, distributed system with individual user devices/servers training models locally and then aggregating their model updates on a trusted central server. Existing systems for FL often use an alway
Externí odkaz:
http://arxiv.org/abs/2405.10968
Hardware accelerators such as GPUs are required for real-time, low-latency inference with Deep Neural Networks (DNN). However, due to the inherent limits to the parallelism they can exploit, DNNs often under-utilize the capacity of today's high-end a
Externí odkaz:
http://arxiv.org/abs/2304.13541
Traditional network resident functions (e.g., firewalls, network address translation) and middleboxes (caches, load balancers) have moved from purpose-built appliances to software-based components. However, L2/L3 network functions (NFs) are being imp
Externí odkaz:
http://arxiv.org/abs/2303.04404
Autor:
Ramakrishnan, Rohit K, Ravichandran, Aravinth Balaji, Mishra, Arpita, Kaushalram, Archana, Hegde, Gopalkrishna, Talabattula, Srinivas, Rohde, Peter P
Quantum information processing has conceptually changed the way we process and transmit information. Quantum physics, which explains the strange behaviour of matter at the microscopic dimensions, has matured into a quantum technology that can harness
Externí odkaz:
http://arxiv.org/abs/2206.15383
Autor:
Ramakrishnan, Rohit K., Ravichandran, Aravinth Balaji, Kaushik, Ishwar, Hegde, Gopalkrishna, Talabattula, Srinivas, Rohde, Peter P.
In the century following its discovery, applications for quantum physics are opening a new world of technological possibilities. With the current decade witnessing quantum supremacy, quantum technologies are already starting to change the ways inform
Externí odkaz:
http://arxiv.org/abs/2206.15376
The Martensitic transformation (MT) in A15 binary-alloy superconductor V_3Si, though studied extensively, has not yet been conclusively linked with a transition to superconductivity. Previous NMR studies have mainly been on powder samples and with li
Externí odkaz:
http://arxiv.org/abs/2204.03729
In reinforcement learning for visual navigation, it is common to develop a model for each new task, and train that model from scratch with task-specific interactions in 3D environments. However, this process is expensive; massive amounts of interacti
Externí odkaz:
http://arxiv.org/abs/2202.02440
Autor:
Ramakrishnan, Santhosh K., Gokaslan, Aaron, Wijmans, Erik, Maksymets, Oleksandr, Clegg, Alex, Turner, John, Undersander, Eric, Galuba, Wojciech, Westbury, Andrew, Chang, Angel X., Savva, Manolis, Zhao, Yili, Batra, Dhruv
We present the Habitat-Matterport 3D (HM3D) dataset. HM3D is a large-scale dataset of 1,000 building-scale 3D reconstructions from a diverse set of real-world locations. Each scene in the dataset consists of a textured 3D mesh reconstruction of inter
Externí odkaz:
http://arxiv.org/abs/2109.08238
Serverless computing is increasingly popular because of its lower cost and easier deployment. Several cloud service providers (CSPs) offer serverless computing on their public clouds, but it may bring the vendor lock-in risk. To avoid this limitation
Externí odkaz:
http://arxiv.org/abs/2106.03601
We introduce environment predictive coding, a self-supervised approach to learn environment-level representations for embodied agents. In contrast to prior work on self-supervised learning for images, we aim to jointly encode a series of images gathe
Externí odkaz:
http://arxiv.org/abs/2102.02337