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- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.14)
- North America > United States (0.04)
- Europe > Germany (0.04)
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Supplementary Material -- Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions
Fast parallel circuits for the quantum fourier transform.
Country:
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.14)
- North America > United States (0.04)
- Europe > Germany (0.04)
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Technology:
Contrastive Learning with Nasty Noise
Contrastive learning has emerged as a powerful paradigm for self-supervised representation learning. This work analyzes the theoretical limits of contrastive learning under nasty noise, where an adversary modifies or replaces training samples. Using PAC learning and VC-dimension analysis, lower and upper bounds on sample complexity in adversarial settings are established. Additionally, data-dependent sample complexity bounds based on the l2-distance function are derived.
2502.17872
Technology: Information Technology > Artificial Intelligence > Machine Learning > Computational Learning Theory (0.56)