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Greatest papers with code

COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting

29 Mar 2016numbbo/coco

We introduce COCO, an open source platform for Comparing Continuous Optimizers in a black-box setting.

MULTIOBJECTIVE OPTIMIZATION

Efficient Continuous Pareto Exploration in Multi-Task Learning

ICML 2020 mit-gfx/ContinuousParetoMTL

We present a novel, efficient method that generates locally continuous Pareto sets and Pareto fronts, which opens up the possibility of continuous analysis of Pareto optimal solutions in machine learning problems.

MULTIOBJECTIVE OPTIMIZATION MULTI-TASK LEARNING

Learning the Pareto Front with Hypernetworks

ICLR 2021 AvivNavon/pareto-hypernetworks

Here, we tackle the problem of learning the entire Pareto front, with the capability of selecting a desired operating point on the front after training.

FAIRNESS MULTIOBJECTIVE OPTIMIZATION MULTI-TARGET REGRESSION MULTI-TASK LEARNING SEMANTIC SEGMENTATION

Pareto Multi-Task Learning

NeurIPS 2019 Xi-L/ParetoMTL

Recently, a novel method is proposed to find one single Pareto optimal solution with good trade-off among different tasks by casting multi-task learning as multiobjective optimization.

MULTIOBJECTIVE OPTIMIZATION MULTI-TASK LEARNING

Multiobjective Optimization Training of PLDA for Speaker Verification

25 Aug 2018sanphiee/MOT-sGPLDA-SRE14

Most current state-of-the-art text-independent speaker verification systems take probabilistic linear discriminant analysis (PLDA) as their backend classifiers.

MULTIOBJECTIVE OPTIMIZATION TEXT-INDEPENDENT SPEAKER VERIFICATION

Max-value Entropy Search for Multi-Objective Bayesian Optimization

NeurIPS 2019 belakaria/MESMO

We consider the problem of multi-objective (MO) blackbox optimization using expensive function evaluations, where the goal is to approximate the true Pareto-set of solutions by minimizing the number of function evaluations.

BAYESIAN OPTIMISATION GLOBAL OPTIMIZATION MULTIOBJECTIVE OPTIMIZATION

ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining

11 Jun 2019ehw-fit/tf-approximate

A suitable approximate multiplier is then selected for each computing element from a library of approximate multipliers in such a way that (i) one approximate multiplier serves several layers, and (ii) the overall classification error and energy consumption are minimized.

MULTIOBJECTIVE OPTIMIZATION

Efficient and Sparse Neural Networks by Pruning Weights in a Multiobjective Learning Approach

31 Aug 2020malena1906/Pruning-Weights-with-Biobjective-Optimization-Keras

We suggest a multiobjective perspective on the training of neural networks by treating its prediction accuracy and the network complexity as two individual objective functions in a biobjective optimization problem.

MULTIOBJECTIVE OPTIMIZATION

How to Evaluate Solutions in Pareto-based Search-Based Software Engineering? A Critical Review and Methodological Guidance

20 Feb 2020taochen/sbse-qi

We then conduct an in-depth analysis of quality evaluation indicators/methods and general situations in SBSE, which, together with the identified issues, enables us to codify a methodological guidance for selecting and using evaluation methods in different SBSE scenarios.

MULTIOBJECTIVE OPTIMIZATION

Pareto-optimal data compression for binary classification tasks

23 Aug 2019tailintalent/distillation

The goal of lossy data compression is to reduce the storage cost of a data set $X$ while retaining as much information as possible about something ($Y$) that you care about.

IMAGE CLUSTERING MULTIOBJECTIVE OPTIMIZATION