arXiv Computer Science @arxiv_cs@qoto.org

Variable importance scores. (arXiv:2102.07765v1 [cs.LG]) http://arxiv.org/abs/2102.07765

Reflecting stochastic dynamics of active-passive crowds in a queueing theory model. (arXiv:2102.07766v1 [math.NA]) http://arxiv.org/abs/2102.07766

Communication-Efficient Distributed Cooperative Learning with Compressed Beliefs. (arXiv:2102.07767v1 [cs.LG]) http://arxiv.org/abs/2102.07767

Posterior-Aided Regularization for Likelihood-Free Inference. (arXiv:2102.07770v1 [cs.LG]) http://arxiv.org/abs/2102.07770

Online learning of Riemannian hidden Markov models in homogeneous Hadamard spaces. (arXiv:2102.07771v1 [cs.LG]) http://arxiv.org/abs/2102.07771

PeriodNet: A non-autoregressive waveform generation model with a structure separating periodic and aperiodic components. (arXiv:2102.07786v1 [eess.AS]) http://arxiv.org/abs/2102.07786

Universal Adversarial Examples and Perturbations for Quantum Classifiers. (arXiv:2102.07788v1 [quant-ph]) http://arxiv.org/abs/2102.07788

A space-time isogeometric method for the partial differential-algebraic system of Biot's poroelasticity model. (arXiv:2102.07798v1 [math.NA]) http://arxiv.org/abs/2102.07798

Ada-SISE: Adaptive Semantic Input Sampling for Efficient Explanation of Convolutional Neural Networks. (arXiv:2102.07799v1 [cs.CV]) http://arxiv.org/abs/2102.07799

Top-$k$ eXtreme Contextual Bandits with Arm Hierarchy. (arXiv:2102.07800v1 [stat.ML]) http://arxiv.org/abs/2102.07800

Neural Network Libraries: A Deep Learning Framework Designed from Engineers' Perspectives. (arXiv:2102.06725v1 [cs.LG]) http://arxiv.org/abs/2102.06725

SOAR: A Synthesis Approach for Data Science API Refactoring. (arXiv:2102.06726v1 [cs.SE]) http://arxiv.org/abs/2102.06726

Operational Annotations: A new method for sequential program verification. (arXiv:2102.06727v1 [cs.SE]) http://arxiv.org/abs/2102.06727

A novel method for object detection using deep learning and CAD models. (arXiv:2102.06729v1 [cs.CV]) http://arxiv.org/abs/2102.06729

Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution. (arXiv:2102.06732v1 [cs.CV]) http://arxiv.org/abs/2102.06732

Revisiting the details when evaluating a visual tracker. (arXiv:2102.06733v1 [cs.CV]) http://arxiv.org/abs/2102.06733

Learning Deep Neural Networks under Agnostic Corrupted Supervision. (arXiv:2102.06735v1 [cs.LG]) http://arxiv.org/abs/2102.06735

Kronecker-factored Quasi-Newton Methods for Convolutional Neural Networks. (arXiv:2102.06737v1 [cs.LG]) http://arxiv.org/abs/2102.06737

Applicability of Random Matrix Theory in Deep Learning. (arXiv:2102.06740v1 [cs.LG]) http://arxiv.org/abs/2102.06740

Discovery of Options via Meta-Learned Subgoals. (arXiv:2102.06741v1 [cs.LG]) http://arxiv.org/abs/2102.06741