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Towards Explaining Image-Based Distribution Shifts

Distribution shift can have fundamental consequences such as signaling a change in the operating environment or significantly reducing the accuracy of downstream models. Thus, understanding such distribution shifts is critical for examining and …

Deep Point Process Destructors

Hyperparameter Selection under Localized Label Noise via Corrupt Validation

Existing research on label noise often focuses on simple uniform or classconditional noise. However, in many real-world settings, label noise is often somewhat systematic rather than completely random. Thus, we first propose a novel label noise model …

Summarization of Twitter Microblogs

Owing to the sheer volume of text generated by a microblog site like Twitter, it is often difficult to fully understand what is being said about various topics. This paper presents algorithms for summarizing microblog documents. Initially, we present …

Towards Undistorted and Noise-free Speech in an MRI Scanner: Correlation Subtraction Followed by Spectral Noise Gating

Noise cancellation in an MRI environment is difficult due to the high noise levels that are in the spectral range of human speech. This paper describes a two-step method to cancel MRI noise that combines operations in both the time domain …

Comparing Twitter Summarization Algorithms for Multiple Post Summaries

Due to the sheer volume of text generated by a micro log site like Twitter, it is often difficult to fully understand what is being said about various topics. In an attempt to understand micro logs better, this paper compares algorithms for …