2021.10.11 Neural papers

10-06-2021	Assemblies of neurons can learn to classify well-separated distributions by Max Dabagia et al
10-05-2021	NEWRON: A New Generalization of the Artificial Neuron to Enhance the Interpretability of Neural Networks by Federico Siciliano et al
10-05-2021	Evolutionary Algorithms for Solving Unconstrained, Constrained and Multi-objective Noisy Combinatorial Optimisation Problems by Aishwaryaprajna et al
10-06-2021	Data-Centric AI Requires Rethinking Data Notion by Mustafa Hajij et al
10-07-2021	Explicitly Multi-Modal Benchmarks for Multi-Objective Optimization by Reiya Hagiwara et al
10-06-2021	StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and Synthesis by Islem Mhiri et al
10-07-2021	Evolutionary Computation-Assisted Brainwriting for Large-Scale Online Ideation by Nobuo Namura et al
10-07-2021	Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design by Ye Yuan et al
10-07-2021	Contextual Sentence Classification: Detecting Sustainability Initiatives in Company Reports by Dan Hirlea et al
10-07-2021	On the Optimal Memorization Power of ReLU Neural Networks by Gal Vardi et al
10-07-2021	Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators by Alexander Shekhovtsov
10-06-2021	Cloud Failure Prediction with Hierarchical Temporary Memory: An Empirical Assessment by Oliviero Riganelli et al
10-07-2021	Universal Approximation Under Constraints is Possible with Transformers by Anastasis Kratsios et al
10-07-2021	GEO satellites on-orbit repairing mission planning with mission deadline constraint using a large neighborhood search-genetic algorithm by Peng Han et al
10-08-2021	A Study of Low-Resource Speech Commands Recognition based on Adversarial Reprogramming by Hao Yen et al
10-05-2021	Neural Network Adversarial Attack Method Based on Improved Genetic Algorithm by Dingming Yang et al
10-06-2021	QTN-VQC: An End-to-End Learning framework for Quantum Neural Networks by Jun Qi et al
10-06-2021	Spike-inspired Rank Coding for Fast and Accurate Recurrent Neural Networks by Alan Jeffares et al