Program

Keynote Talk: NLP for Close Domain Applications with Real World Data: an hybrid approach to jointly leverage prior domain knowledge, reasoning techniques and deep learning

Sentiment Risk Premia in the Cross-Section of Global Equity

GPU Accelerated Data Preparation for Limit Order Book Modeling

A new approach to Early Warning Systems for small European banks

Gradient Bias to solve the Generalization Limit of Genetic Algorithms through hybridization with Reinforcement Learning

Investigating the Compositional Structure of Deep Neural Networks

Optimal Scenario-Tree Selection for Multistage Stochastic Programming

CMAC: Clustering class association rules to form a Compact and Meaningful Associative Classifier

Combinatorial reliability-based optimization of nonlinear finite element model using an artificial neural network-based approximation

Driving Subscriptions Through User Behavior Modelling and Prediction at Bloomberg Media

Deep 3D Convolution Neural Network for Alzheimer’s Detection

Variance Loss in Variational Autoencoders

Learn to Move Through a Combination of Policy Gradient Algorithms: DDPG, D4PG, and TD3

Identifying Key miRNA–mRNA Regulatory Modules in Cancer Using Sparse Multivariate Factor Regression

Wasserstein Embeddings for Nonnegative Matrix Factorization

Automatic Setting of DNN Hyper-Parameters by Mixing Bayesian Optimization and Tuning Rules

Revisiting clustering as matrix factorisation on the Stiefel manifold

Privacy preserving Deep Learning framework in Fog computing

A Krill Herd Algorithm for the Multi-objective Energy Reduction Multi-Depot Vehicle Routing Problem

XM HeatForecast: Heating Load Forecasting in Smart District Heating Networks

Injective Domain Knowledge in NNs for Transprecision Computing

Evaluating the Impact of Training Loss on MR to Synthetic CT Conversion

A location-routing based solution approach for reorganizing postal collection operations in rural areas

Dynamic selection of classifiers applied to high-dimensional small-instance data sets: problems and challenges

Caching suggestions using Reinforcement Learning

Keynote Talk: Technical challenges of Ethical ML

Using Hessians as a Regularization Technique

Should simplicity be always preferred to complexity in supervised machine learning?

Understanding production process productivity in glass container industry: a big data approach

Generative Fourier-based Auto-Encoders: Preliminary Results

A Double-Dictionary Approach Learns Component Means and Variances for V1 Encoding

Steplength and mini-batch size selection in Stochastic Gradient Methods

Who Accepts Information Measures

Semantic Segmentation of Neuronal Bodies in Fluorescence Microscopy Using a 2D+3D CNN Training Strategy with Sparsely Annotated Data

Analyzing Data with Lagrange multipliers methods

Policy Feedback in Deep Reinforcement Learning to exploit expert knowledg

BcRAIN: A Deep Learning based approach for B-cell repertoire description

Study on the class of Jarratt-like iterative methods

From Business Curated Products to Algorithmically Generated

Future of HR from 2020: Machine Learning

Deep Quarantine for Suspicious Mail

Neural Random Projection: From the Initial Task to the Input Similarity Problem

Sparsity Meets Robustness: Channel Pruning for the Feynman- Kac Formalism Principled Robust Deep Neural Nets

Keynote Talk: Safety and robustness for deep learning with provable guarantees

Structural and Functional Representativity of GANs for Data Generation in Sequential Decision Making

Image Features Anonymization for Privacy aware Machine Learning

Prediction of Spot prices in Nord Pool's Day-ahead market using Machine and Deep learning

Robust Generative Restricted Kernel Machines using Weighted Conjugate Feature Duality

Unit Propagation by Means of Coordinate-Wise Minimization

A learning-based mathematical programming formulation for the automatic configuration of optimization solvers

Discovering Travelers' Purchasing Behavior from Public Transport Data

Multi-Kernel Covariance Terms in Multi-Output Support Vector Machines

FoodViz: Visualization of Food Entities Linked Across Different Standards

Learning Controllers for Adaptive Spreading of Carbon Fiber Tows

Ensemble Kalman Filter optimizing Deep Neural Networks: An alternative approach to non-performing Gradient Descent

Effects of random seeds on the accuracy of Convolutional Neural Networks

Benchmarking Deep Learning Models for Driver Distraction Detection

Safer Reinforcement Learning for Agents in Industrial Grid- Warehousing

Target-aware Prediction of Tool Usage in Sequential Repair Tasks

A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry

Exploring Gaps in DeepFool in Search of More Effective Adversarial Perturbations

A forecasting model to predict the demand of roses in an Ecuadorian small business under uncertain scenarios

Skin Lesion Diagnosis with Imbalanced ECOC Ensembles

Learning Objective Boundaries for Constraint Optimization Problems

A Generalized Quadratic Loss for SVM and Deep Neural Networks

Hierarchical Representation and Graph Convolutional Networks for the Prediction of Protein–Protein Interaction Sites

Brain-inspired Spike Timing Model of Dynamic Visual Information Perception and Decision Making with STDP and Reinforcement Learning

PlattForm: Parallel Spoken Corpus of Middle West German Dialects with Web-Based Interface

Keynote Talk: Machine Learning with quantum computers

Keynote Talk: Viral Metabolic Reprogramming

Parameterized Structured Pruning for Deep Neural Networks

Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1

Optimal Broadcast Strategy in Homogeneous Point-to-Point Networks

State Representation Learning from Demonstration

Chronologically guided deep network for remaining useful life estimation

High-Dimensional Constrained Discrete Multi-Objective Optimization Using Surrogates

Sparse Perturbations for Improved Convergence in SZO Optimization

On the Reliability of Dynamical Stochastic Binary Systems

Coking coal railway transportation forecasting using ensembles of ElasticNet, LightGBM, and Facebook Prophet

Heuristic Search in LegalTech: Dynamic Allocation of Legal Cases to Legal Staff

Multi-parameter Regression of Photovoltaic Systems using Selection of Variables with the Method: Recursive Feature Elimination for Ridge, Lasso and Bayes

Automatic curriculum recommendation for employees

Fast hyperparameter tuning for support vector machines with stochastic gradient descent

Lottery Ticket Hypothesis: Placing the k-orrect bets

Black Box Algorithm Selection by Convolutional Neural Network

A Fast Genetic Algorithm for the Max Cut-Clique Problem

The Intellectual Structure of Business Analytics: 2002~2019

Reinforcement Learning for Playing WrapSlide

A Unified Approach to Anomaly Detection

On Bayesian Search for the Feasible Space Under Computationally Expensive Constraints

Unsupervisedly Learned Representations – Should the Quest be Over?

Efficient text processing via Context Triggered Piecewise Hashing algorithm for spam detection

Limits of Transfer Learning

Automatic Classification of low Angle Fuze-Quick Craters Using Deep Learning

Gravitational Forecast Reconciliation

Keynote Talk: "A problem for every solution" - on adversarial methods for AI Ethics

Pareto-Weighted-Sum-Tuning: Learning-to-Rank for Pareto Optimization Problems

Quantifying Local Energy Demand through Pollution Analysis

Reliable Solution of Multidimensional Stochastic Problems Using Metamodels

Univariate Time Series Anomaly Labelling Algorithm

Keynote Talk: Promises and Challenges of Transfer Learning

Explainable AI as a Social Microscope: A Case Study on Academic Performance

On Graph Learning with Neural Networks

Machine Learning and Statistical Models for the Prevalence of Multiple Sclerosis

Global Convergence of Sobolev Training for Overparametrized Neural Network

Challenges in Real-Life Face Recognition With Heavy Makeup and Occlusions Using Deep Learning Algorithms

An error-based addressing architecture for dynamic model learning

Keynote Talk: Virtualization and Deep Learning

A fast and efficient smoothing approach to LASSO regression and an application in statistical genetics: polygenic risk scores for Chronic obstructive pulmonary disease (COPD)

An application of Machine Learning to study utilities expenses in the Brazilian Navy

Adjusted Measures for Feature Selection Stability for Data Sets with Similar Features

Estimating the F1 score for Learning from Positive and Unlabeled Examples

Closing

The Speech Processing Platform at Uber

Robust and Sparse Support Vector Machines via Mixed Integer Programming

l1 Regularized Robust and Sparse Linear Modeling Using Discrete Optimization

Importance Weighting of Diagnostic Trouble Codes for Anomaly Detection

Welcome

Keynote Talk: From Probabilistic Logic Programming to Neural Symbolic Computation

Keynote Talk: Constructive Machine Learning

Keynote Talk: Relational Neural Machines

Coffee break

Keynote Talk: Teaching the Old Dog New Tricks: Constraint Support in Classical Supervised Learning via Declarative Optimization

Keynote Talk: Neural Symbolic Computing for Trusted AI

Round Table/Closing Remarks