Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case. Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions. Workload Prediction of Business Processes – An Approach Based on Process Mining and Recurrent Neural Networks. Dynamic Inference: A New Approach Toward Efficient Video Action Recognition …

Learning to Guide Random Search. Bio-Inspired Hashing for Unsupervised Similarity Search. Detecting malicious PDF using CNN. DeepV2D: Video to Depth with Differentiable Structure from Motion. Unsupervised Data Augmentation for Consistency Training. A Learning-based Iterative Method for Solving Vehicle Routing Problems. Improved Training Techniques …

Towards Stable and Efficient Training of Verifiably Robust Neural Networks. Generating Dialogue Responses From A Semantic Latent Space. Walking on the Edge: Fast, Low-Distortion Adversarial Examples. Shifted and Squeezed 8-bit Floating Point format for Low-Precision Training of Deep Neural Networks. Automatically Learning Feature Crossing from Mode …

Prestopping: How Does Early Stopping Help Generalization Against Label Noise?. Transferring Optimality Across Data Distributions via Homotopy Methods. Scalable and Order-robust Continual Learning with Additive Parameter Decomposition. Coloring graph neural networks for node disambiguation. SMiRL: Surprise Minimizing RL in Entropic Environments. Vis …

Theory and Evaluation Metrics for Learning Disentangled Representations. LSTOD: Latent Spatial-Temporal Origin-Destination prediction model and its applications in ride-sharing platforms. TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear Subspaces. Unsupervised Model Selection for Variational Disentan …

Disentangling Factors of Variations Using Few Labels. Critical initialisation in continuous approximations of binary neural networks. Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks. Stochastic Gradient Descent with Biased but Consistent Gradient Estimators. The Sooner The Better: Investigating Structu …

On Need for Topology-Aware Generative Models for Manifold-Based Defenses. Deep k-NN for Noisy Labels. Visual Interpretability Alone Helps Adversarial Robustness. Learning to Rank Learning Curves. Towards Controllable and Interpretable Face Completion via Structure-Aware and Frequency-Oriented Attentive GANs. An Empirical and Comparative Analysis of …

Deep automodulators. GLAD: Learning Sparse Graph Recovery. Regional based query in graph active learning. A critical analysis of self-supervision, or what we can learn from a single image. FLAT MANIFOLD VAES. PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search. Detecting Extrapolation with Local Ensembles. DBA: Distribute …

Retrieving Signals in the Frequency Domain with Deep Complex Extractors. Learning Cross-modal Context Graph for Visual Grounding. Differentially Private Mixed-Type Data Generation For Unsupervised Learning. HighRes-net: Multi-Frame Super-Resolution by Recursive Fusion. Cost-Effective Testing of a Deep Learning Model through Input Reduction. Learnin …