Zobrazeno 1 - 10
of 371
pro vyhledávání: '"C.1.4"'
Autor:
Gao, Jeffrey, Kainen, Paul C.
A permutation of the elements of a graph is a {\it construction sequence} if no edge is listed before either of its endpoints. The complexity of such a sequence is investigated by finding the delay in placing the edges, an {\it opportunity cost} for
Externí odkaz:
http://arxiv.org/abs/2412.00212
Recent research has shown that large language models (LLMs) can utilize low-precision floating point (FP) quantization to deliver high efficiency while maintaining original model accuracy. In particular, recent works have shown the effectiveness of n
Externí odkaz:
http://arxiv.org/abs/2411.18065
The advent of foundation models have revolutionized various fields, enabling unprecedented task accuracy and flexibility in computational linguistics, computer vision and other domains. Attention mechanism has become an essential component of foundat
Externí odkaz:
http://arxiv.org/abs/2411.17720
Parallel real-time embedded applications can be modelled as directed acyclic graphs (DAGs) whose nodes model subtasks and whose edges model precedence constraints among subtasks. Efficiently scheduling such parallel tasks can be challenging in itself
Externí odkaz:
http://arxiv.org/abs/2410.17563
Large Language Models (LLMs) have demonstrated remarkable performance in various natural language processing tasks. However, the training of these models is computationally intensive and susceptible to faults, particularly in the attention mechanism,
Externí odkaz:
http://arxiv.org/abs/2410.11720
Federated Learning (FL) facilitates data privacy by enabling collaborative in-situ training across decentralized clients. Despite its inherent advantages, FL faces significant challenges of performance and convergence when dealing with data that is n
Externí odkaz:
http://arxiv.org/abs/2410.03499
Federated learning faces a critical challenge in balancing communication efficiency with rapid convergence, especially for second-order methods. While Newton-type algorithms achieve linear convergence in communication rounds, transmitting full Hessia
Externí odkaz:
http://arxiv.org/abs/2409.15216
Publikováno v:
IEEE SPAWC 2024
Upcoming physical layer (PHY) processing solutions, leveraging multiple-input multiple-output (MIMO) advances, are expected to support broad transmission bandwidths and the concurrent transmission of multiple information streams. However, the inheren
Externí odkaz:
http://arxiv.org/abs/2408.13128
Autor:
Pierro, Alessandro, Stratmann, Philipp, Guerra, Gabriel Andres Fonseca, Risbud, Sumedh, Shea, Timothy, Mangalore, Ashish Rao, Wild, Andreas
In this article, we describe an algorithm for solving Quadratic Unconstrained Binary Optimization problems on the Intel Loihi 2 neuromorphic processor. The solver is based on a hardware-aware fine-grained parallel simulated annealing algorithm develo
Externí odkaz:
http://arxiv.org/abs/2408.03076
Transformer-based models have emerged as one of the most widely used architectures for natural language processing, natural language generation, and image generation. The size of the state-of-the-art models has increased steadily reaching billions of
Externí odkaz:
http://arxiv.org/abs/2405.10480