Technology-assisted review (TAR) is an important industrial application of information retrieval (IR) and machine learning (ML). While a small TAR research community exists, the complexity of TAR software and workflows is a major barrier to entry. Dr...
Machine Learning to determine Customer Lifetime Value in a contractual or non-contractual setting. (⭐ 8)
The general solution is to use a STUN server to determine their port mapping. Machine A sends a packet form port X to STUN. The router translated the port to Y, and the STUN server sees this and …
Clustering is a fundamental task in the computer vision and machine learning community. Although various methods have been proposed, the performance of existing approaches drops dramatically when handling incomplete high-dimensional data (which is co...
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. (⭐ 1879)
suffices to consider positive numbers. For the usual round-to-nearest kind of rounding, the absolute rounding error is at most half the spacing, or b − ( p −
Points: 108 | Comments: 17 | Author: dedalus
This study presents a real-world canine heart sound dataset and evaluates SoNUS version 3.2.x, a machine learning algorithm for preliminary cardiac analysis using smartphone microphone recordings. More than one hundred recordings were collected from...
Calibrated uncertainty estimates in machine learning are crucial to many fields such as autonomous vehicles, medicine, and weather and climate forecasting. While there is extensive literature on uncertainty calibration for classification, the classif...
Machine learning classifiers are probabilistic in nature, and thus inevitably involve uncertainty. Predicting the probability of a specific input to be correct is called uncertainty (or confidence) estimation and is crucial for risk management. Post-...
May 10, 2023 · “Step-bro, can you help me?” The words woke me from my nap like a slap to the face. I sat up in confusion, groggily wiping the sleep from my eyes as I looked around the dim room. The …
Child Sexual Abuse Media (CSAM) is any visual record of a sexually-explicit activity involving minors. CSAM impacts victims differently from the actual abuse because the distribution never ends, and images are permanent. Machine learning-based soluti...
As the curation of data for machine learning becomes increasingly automated, dataset tampering is a mounting threat. Backdoor attackers tamper with training data to embed a vulnerability in models that are trained on that data. This vulnerability is...
The training covers introduction to Julia, vector and array operations in Julia, followed by introductory machine learning techniques and applications. The course then takes a deep dive into introducing …
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Global biodiversity is declining at an unprecedented rate, yet little information is known about most species and how their populations are changing. Indeed, some 90% of Earth's species are estimated to be completely unknown. Machine learning has rec...
While preference modelling is becoming one of the pillars of machine learning, the problem of preference explanation remains challenging and underexplored. In this paper, we propose \textsc{Pref-SHAP}, a Shapley value-based model explanation framewor...
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From CNNs to attention mechanisms, encoding inductive biases into neural networks has been a fruitful source of improvement in machine learning. Adding auxiliary losses to the main objective function is a general way of encoding biases that can help...