Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox
Neural Information Processing Systems
Finally, we conclude by highlighting the significant applications of long-tailed learning and identifying several promising future directions.
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Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously
Neural Information Processing Systems
Ideally, the obtained unlearnability can prevent algorithms from training usable models.
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Order-Independence Without Fine Tuning
Reid McIlroy-Young, Katrina Brown, Conlan Olson, Linjun Zhang, Cynthia Dwork
Neural Information Processing Systems
Unlike humans, these ' Large Language Models ' (LLMs) are highly sensitive to small changes in their inputs, leading to unwanted inconsistency in their behavior.
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