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Learning-Augmented Algorithms for the Bahncard Problem
In this paper, we study learning-augmented algorithms for the Bahncard problem.
Oracle-EfficientDifferentiallyPrivateLearningwith PublicData
Due to statistical lower bounds on the learnability of many function classes under privacy constraints, there has been recent interest in leveraging public data to improve the performance of private learning algorithms.
Efficient Generative LLM Inference with R ecallable Key-V al ue Eviction
Large Language Models (LLMs) are widely used in today's tasks of natural language processing.
Matching the Statistical Query Lower Bound for k-Sparse Parity Problems with Sign Stochastic Gradient Descent
's in this subset is even or odd.
T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition Chen Y eh 1 You-Ming Chang 1 Wei-Chen Chiu 1 Ning Y u
Warning: This paper contains inappropriate/harmful visual contents. While widespread access to the Internet and the rapid advancement of generative models boost people's creativity and productivity, the risk of encountering inappropriate or harmful content also increases.