Show newer

Novelty Search in representational space for sample efficient exploration. (arXiv:2009.13579v1 [cs.LG]) arxiv.org/abs/2009.13579

Apollo: An Adaptive Parameter-wise Diagonal Quasi-Newton Method for Nonconvex Stochastic Optimization. (arXiv:2009.13586v1 [cs.LG]) arxiv.org/abs/2009.13586

Quantile Regression Neural Networks: A Bayesian Approach. (arXiv:2009.13591v1 [math.ST]) arxiv.org/abs/2009.13591

Forecasting Short-term load using Econometrics time series model with T-student Distribution. (arXiv:2009.13595v1 [q-fin.ST]) arxiv.org/abs/2009.13595

Anomaly Detection and Sampling Cost Control via Hierarchical GANs. (arXiv:2009.13598v1 [cs.LG]) arxiv.org/abs/2009.13598

Calibration methods for spatial Data. (arXiv:2009.13629v1 [stat.AP]) arxiv.org/abs/2009.13629

A General Bayesian Model for Heteroskedastic Data with Fully Conjugate Full-Conditional Distributions. (arXiv:2009.13636v1 [stat.ME]) arxiv.org/abs/2009.13636

Regressor: A C program for Combinatorial Regressions. (arXiv:2009.12386v1 [stat.AP]) arxiv.org/abs/2009.12386

Why have a Unified Predictive Uncertainty? Disentangling it using Deep Split Ensembles. (arXiv:2009.12406v1 [cs.LG]) arxiv.org/abs/2009.12406

Skew Brownian Motion and Complexity of the ALPS Algorithm. (arXiv:2009.12424v1 [math.PR]) arxiv.org/abs/2009.12424

A Generic Framework for Clustering Vehicle Motion Trajectories. (arXiv:2009.12443v1 [cs.LG]) arxiv.org/abs/2009.12443

Theoretical Justification of the Bi Error Method. (arXiv:2009.12453v1 [stat.ME]) arxiv.org/abs/2009.12453

A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting. (arXiv:2009.12469v1 [cs.LG]) arxiv.org/abs/2009.12469

Constructing Confidence Intervals for the Signals in Sparse Phase Retrieval. (arXiv:2009.12487v1 [stat.ME]) arxiv.org/abs/2009.12487

SEMI: Self-supervised Exploration via Multisensory Incongruity. (arXiv:2009.12494v1 [cs.LG]) arxiv.org/abs/2009.12494

Flight-connection Prediction for Airline Crew Scheduling to Construct Initial Clusters for OR Optimizer. (arXiv:2009.12501v1 [cs.LG]) arxiv.org/abs/2009.12501

Near-Optimal MNL Bandits Under Risk Criteria. (arXiv:2009.12511v1 [cs.LG]) arxiv.org/abs/2009.12511

Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control. (arXiv:2009.11891v1 [stat.ME]) arxiv.org/abs/2009.11891

Bootstrapped Q-learning with Context Relevant Observation Pruning to Generalize in Text-based Games. (arXiv:2009.11896v1 [cs.LG]) arxiv.org/abs/2009.11896

Adversarial Examples in Deep Learning for Multivariate Time Series Regression. (arXiv:2009.11911v1 [cs.LG]) arxiv.org/abs/2009.11911

Show older
Qoto Mastodon

QOTO: Question Others to Teach Ourselves
An inclusive, Academic Freedom, instance
All cultures welcome.
Hate speech and harassment strictly forbidden.