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Jan 26, 2021
Machine Learning
Applications

SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials wit…

Phase I clinical trials are designed to test the safety (non-toxicity) of drugs and find the maximum tolerated dose (MTD). This task becomes signific…
Jan 26, 2021
Computer Vision

Deep Burst Super-Resolution

While single-image super-resolution (SISR) has attracted substantial interest in recent years, the proposed approaches are limited to learning image …
Jan 26, 2021
Computer Vision
Graphics

Neural Geometric Level of Detail: Real-time Rendering with Implicit 3…

Neural signed distance functions (SDFs) are emerging as an effective representation for 3D shapes. State-of-the-art methods typically encode the SDF …
Jan 26, 2021
Machine Learning

Unsupervised clustering of series using dynamic programming and neura…

Following the work of arXiv:2101.09512, we are interested in clustering a given multi-variate series in an unsupervised manner. We would like to segm…
Jan 26, 2021
Optimization and Control
Machine Learning
Systems and Control

Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: Th…

This paper considers the problem of multi-agent distributed linear regression in the presence of system noises. In this problem, the system comprises…
Jan 26, 2021
Artificial Intelligence

Investment vs. reward in a competitive knapsack problem

Natural selection drives species to develop brains, with sizes that increase with the complexity of the tasks to be tackled. Our goal is to investiga…
Jan 26, 2021
Neurons and Cognition
Artificial Intelligence

Predicting the future with a scale-invariant temporal memory for the …

In recent years it has become clear that the brain maintains a temporal memory of recent events stretching far into the past. This paper presents a n…
Jan 26, 2021
Computation and Language

"Laughing at you or with you": The Role of Sarcasm in Shaping the D…

Detecting arguments in online interactions is useful to understand how conflicts arise and get resolved. Users often use figurative language, such as…
Jan 26, 2021
Machine Learning

Incremental Search Space Construction for Machine Learning Pipeline …

Automated machine learning (AutoML) aims for constructing machine learning (ML) pipelines automatically. Many studies have investigated efficient met…
Jan 26, 2021
Computation and Language

Attention Can Reflect Syntactic Structure (If You Let It)

Since the popularization of the Transformer as a general-purpose feature encoder for NLP, many studies have attempted to decode linguistic structure …
Jan 26, 2021
Image and Video Processing
Computer Vision

Learning-Based Patch-Wise Metal Segmentation with Consistency Check

Metal implants that are inserted into the patient's body during trauma interventions cause heavy artifacts in 3D X-ray acquisitions. Metal Artifact R…
Jan 26, 2021
Computer Vision

Nondiscriminatory Treatment: a straightforward framework for multi-hu…

Multi-human parsing aims to segment every body part of every human instance. Nearly all state-of-the-art methods follow the "detection first" or "seg…
Jan 26, 2021
Methodology
Statistics Theory
Applications
Machine Learning

USP: an independence test that improves on Pearson's chi-squared and …

We present the $U$-Statistic Permutation (USP) test of independence in the context of discrete data displayed in a contingency table. Either Pearson'…
Jan 26, 2021
Image and Video Processing
Computer Vision
Machine Learning

Blind Image Denoising and Inpainting Using Robust Hadamard Autoencode…

In this paper, we demonstrate how deep autoencoders can be generalized to the case of inpainting and denoising, even when no clean training data is a…
Jan 26, 2021
Computation and Language

Spark NLP: Natural Language Understanding at Scale

Spark NLP is a Natural Language Processing (NLP) library built on top of Apache Spark ML. It provides simple, performant and accurate NLP annotations…
Jan 26, 2021
Computer Vision
Machine Learning

Revisiting Locally Supervised Learning: an Alternative to End-to-end …

Due to the need to store the intermediate activations for back-propagation, end-to-end (E2E) training of deep networks usually suffers from high GPUs…
Jan 26, 2021
Computer Vision

In this paper, we propose ProDA which resorts to prototypes to online denoise the pseudo labels and learn the compact feature space for the target domain. Knowledge distillation to a self-supervised pretrained model further boosts the performance. T…

Prototypical Pseudo Label Denoising and Target Structure Learning for…

Self-training is a competitive approach in domain adaptive segmentation, which trains the network with the pseudo labels on the target domain. Howeve…
Jan 26, 2021
Computer Vision
Artificial Intelligence

Learning Spatial and Spatio-Temporal Pixel Aggregations for Image and…

Existing denoising methods typically restore clear results by aggregating pixels from the noisy input. Instead of relying on hand-crafted aggregation…
Jan 26, 2021
Computer Vision
Multimedia
Image and Video Processing

We have proposed an effective and efficient model for predicting the subjective quality of user-generated videos, which we call the Rapid and Accurate Video Quality Evaluator (RAPIQUE). The model, for the first time, leverages a composite of spatio-…

RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generate…

Blind or no-reference video quality assessment of user-generated content (UGC) has become a trending, challenging, unsolved problem. Accurate and eff…
Jan 26, 2021
Machine Learning

In this paper we considered meta-learning strategies for nonparametric CATE estimation, theoretically analyzed their properties, and implemented them using NNs. We demonstrated that while the DR-learner is asymptotically optimal in theory, both the …

Nonparametric Estimation of Heterogeneous Treatment Effects: From The…

The need to evaluate treatment effectiveness is ubiquitous in most of empirical science, and interest in flexibly investigating effect heterogeneity …
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