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Attention Based Simple Primitives for Open World Compositional Zero Shot Lear...
Compositional Zero-Shot Learning (CZSL) aims to predict unknown compositions made up of attribute and object pairs. -
SMARTPASTE Dataset
The dataset contains 4.8 million lines of C# code from 27 projects. -
SMARTPASTE
The SMARTPASTE task is a challenge for machine learning modeling of source code, that requires to learn (some) semantics of programs. -
Matching Map Recovery with an Unknown Number of Outliers
The dataset used in the paper is a set of feature-vectors from two sets of d-dimensional noisy feature-vectors. -
Large-scale Machine Learning Dataset
The dataset used in this paper is a large-scale machine learning dataset. -
Quantum Adiabatic Algorithm Design using Reinforcement Learning
The dataset used in the paper is a reinforcement learning-based approach for automated quantum adiabatic algorithm design. The dataset consists of Grover search and 3-SAT problems. -
RL-CZSL-ATTR and RL-CZSL-ACT
Two large-scale benchmark datasets for reference-limited compositional zero-shot learning (RL-CZSL). -
Kaggle Dataset
The dataset used in the paper is a publicly available dataset from Kaggle, used for demonstrating the effectiveness of the Lai loss function. -
effective dimension of a statistical model
The dataset is not explicitly described in the paper, but it is mentioned that it is used to test the proposed notion of effective dimension. -
Abalone dataset
The dataset used in this paper is the Abalone dataset, which is a multivariate dataset containing information about abalone, a type of sea creature. -
Machine Learning and Deep Learning Methods for Cybersecurity
Machine learning and deep learning methods for cybersecurity -
An Enhanced Electrocardiogram Biometric Authentication System Using Machine L...
ECG-based authentication system using regression as a machine learning technique -
CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq
Single-cell RNA sequencing (scRNA-seq) has the potential to provide powerful, high-resolution signatures to inform disease prognosis and precision medicine. -
Rapid detection of rare events from in situ X-ray diffraction data using mach...
High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk... -
Dataset for ℓp subspace approximation
The dataset used in this paper is a set of points in d-dimensional space, with n points in total. -
Normal Linear Model
The dataset used in the paper is a normal linear model: Y = Xβ + (cid:15), (cid:15) ∼ N (0, σ2I), where Y is an N dimensional response vector, X is an N ×D dimensional design... -
FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine L...
FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines -
Millionsong
The dataset used in the paper is a ridge regression problem (Millionsong) and a support vector machine (RCV1) and a matrix completion problem (Netflix) on a large-scale... -
Therapeutics Data Commons
Therapeutics Data Commons (TDC) is a machine learning dataset and task for drug discovery and development.
