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Model Selection

113 papers with code ยท Methodology

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Revealing consensus and dissensus between network partitions

28 May 2020

As an attempt to extract understanding from a population of alternative solutions, many methods exist to establish a consensus among them in the form of a single partition "point estimate" that summarizes the whole distribution.

COMMUNITY DETECTION MODEL SELECTION

Selective Inference for Latent Block Models

27 May 2020

Specifically, we construct a statistical test on a set of row and column cluster memberships of a latent block model, which is given by a squared residue minimization algorithm.

MODEL SELECTION

On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law

19 May 2020

Out-of-distribution (OOD) testing is increasingly popular for evaluating a machine learning system's ability to generalize beyond the biases of a training set.

MODEL SELECTION QUESTION ANSWERING VISUAL QUESTION ANSWERING

Marginal likelihood computation for model selection and hypothesis testing: an extensive review

17 May 2020

This is an up-to-date introduction to, and overview of, marginal likelihood computation for model selection and hypothesis testing.

MODEL SELECTION

Systematic Ensemble Model Selection Approach for Educational Data Mining

13 May 2020

A plethora of research has been done in the past focusing on predicting student's performance in order to support their development.

MODEL SELECTION

Robust Lasso-Zero for sparse corruption and model selection with missing covariates

12 May 2020

The use of Robust Lasso-Zero is showcased for variable selection with missing values in the covariates.

MODEL SELECTION

Lossy Compression with Distortion Constrained Optimization

8 May 2020

We argue that the constrained optimization method of Rezende and Viola, 2018 is a lot more appropriate for training lossy compression models because it allows us to obtain the best possible rate subject to a distortion constraint.

IMAGE COMPRESSION MODEL SELECTION

Spiking Neural Networks Hardware Implementations and Challenges: a Survey

4 May 2020

Neuromorphic computing is henceforth a major research field for both academic and industrial actors.

MODEL SELECTION

A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label Learning

3 May 2020

In real-world applications, learning from data with multi-view and multi-label inevitably confronts with three challenges: missing labels, incomplete views, and non-aligned views.

MODEL SELECTION MULTI-LABEL LEARNING

DriveML: An R Package for Driverless Machine Learning

1 May 2020

In recent years, the concept of automated machine learning has become very popular.

AUTOML FEATURE ENGINEERING MODEL SELECTION