Explainable AI (XAI): Core ideas, techniques, and solutions

R Dwivedi, D Dave, H Naik, S Singhal, R Omer… - ACM Computing …, 2023‏ - dl.acm.org
As our dependence on intelligent machines continues to grow, so does the demand for more
transparent and interpretable models. In addition, the ability to explain the model generally …

Distributed artificial intelligence empowered by end-edge-cloud computing: A survey

S Duan, D Wang, J Ren, F Lyu, Y Zhang… - … Surveys & Tutorials, 2022‏ - ieeexplore.ieee.org
As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …

Ring attention with blockwise transformers for near-infinite context

H Liu, M Zaharia, P Abbeel - arxiv preprint arxiv:2310.01889, 2023‏ - arxiv.org
Transformers have emerged as the architecture of choice for many state-of-the-art AI
models, showcasing exceptional performance across a wide range of AI applications …

Towards understanding biased client selection in federated learning

YJ Cho, J Wang, G Joshi - International Conference on …, 2022‏ - proceedings.mlr.press
Federated learning is a distributed optimization paradigm that enables a large number of
resource-limited client nodes to cooperatively train a model without data sharing. Previous …

Federated learning on non-IID data: A survey

H Zhu, J Xu, S Liu, Y ** - Neurocomputing, 2021‏ - Elsevier
Federated learning is an emerging distributed machine learning framework for privacy
preservation. However, models trained in federated learning usually have worse …

Privacy-preserving Byzantine-robust federated learning via blockchain systems

Y Miao, Z Liu, H Li, KKR Choo… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Federated learning enables clients to train a machine learning model jointly without sharing
their local data. However, due to the centrality of federated learning framework and the …

[HTML][HTML] RNN-LSTM: From applications to modeling techniques and beyond—Systematic review

SM Al-Selwi, MF Hassan, SJ Abdulkadir… - Journal of King Saud …, 2024‏ - Elsevier
Abstract Long Short-Term Memory (LSTM) is a popular Recurrent Neural Network (RNN)
algorithm known for its ability to effectively analyze and process sequential data with long …

[PDF][PDF] Internlm: A multilingual language model with progressively enhanced capabilities

ILM Team - 2023‏ - static.aminer.cn
We present InternLM, a multilingual foundational language model with 104B parameters.
InternLM is pre-trained on a large corpora with 1.6 T tokens with a multi-phase progressive …

When will RNA get its AlphaFold moment?

B Schneider, BA Sweeney, A Bateman… - Nucleic Acids …, 2023‏ - academic.oup.com
The protein structure prediction problem has been solved for many types of proteins by
AlphaFold. Recently, there has been considerable excitement to build off the success of …

The evolution of distributed systems for graph neural networks and their origin in graph processing and deep learning: A survey

J Vatter, R Mayer, HA Jacobsen - ACM Computing Surveys, 2023‏ - dl.acm.org
Graph neural networks (GNNs) are an emerging research field. This specialized deep
neural network architecture is capable of processing graph structured data and bridges the …