A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Maryam M. Najafabadi, Flavio Villanustre, Taghi M. Khoshgoftaar, et al.
Explores how deep learning addresses big data analytics challenges like pattern extraction, semantic indexing, and scalability.
Xiaoyuan Su, Taghi M. Khoshgoftaar
A comprehensive survey of collaborative filtering techniques, categorizing them into memory-based, model-based, and hybrid approaches while addressing key challenges like data sparsity and scalability.
Unknown
ConvNeXt modernizes standard ResNet with Transformer-inspired training and design, achieving competitive accuracy and scalability.
Unknown
This paper empirically studies the design of vision Mixture-of-Experts (MoE) models, providing insights into routing strategies and expert architectures for improved scalability.
Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, et al.
Random parameterized quantum circuits cause exponentially vanishing gradients (barren plateaus) in hybrid quantum-classical training, hindering scalability beyond a few qubits.