Optimistic bounds for multi-output prediction. Learning Object Placements For Relational Instructions by Hallucinating Scene Representations. Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning. Deontological Ethics By Monotonicity Shape Constraints. Implementing Dynamic Answer Set Programming. A scheme for automatic differe …

SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency. Processing topical queries on images of historical newspaper pages. Learning Functionally Decomposed Hierarchies for Continuous Control Tasks. Hierarchical Reinforcement Learning as a Model of Human Task Interleaving. Effect of Confidence and E …

On the Convex Behavior of Deep Neural Networks in Relation to the Layers’ Width. Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation. AutoFCL: Automatically Tuning Fully Connected Layers for Handling Small Dataset. Stochastic Online Optimization using Kalman Recursion. ADAMT: A Stochastic Optimization with Trend …

Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling. Discovering Motor Programs by Recomposing Demonstrations. Representing Unordered Data Using Multiset Automata and Complex Numbers. Evaluating Lossy Compression Rates of Deep Generative Models. Attentive Sequential Neural Processes. Controlling generative models with continuou …

Equivariant Entity-Relationship Networks. Adversarial Inductive Transfer Learning with input and output space adaptation. Are Transformers universal approximators of sequence-to-sequence functions?. Generalizing Reinforcement Learning to Unseen Actions. Leveraging Simple Model Predictions for Enhancing its Performance. Learning to Transfer via Mode …

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 …

Machine Truth Serum. Adversarial training with perturbation generator networks. Conditional Invertible Neural Networks for Guided Image Generation. To Relieve Your Headache of Training an MRF, Take AdVIL. Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension. Incorporating BERT into Neura …

Learning to Reach Goals Without Reinforcement Learning. HOW IMPORTANT ARE NETWORK WEIGHTS? TO WHAT EXTENT DO THEY NEED AN UPDATE?. Universal Adversarial Attack Using Very Few Test Examples. THE EFFECT OF ADVERSARIAL TRAINING: A THEORETICAL CHARACTERIZATION. Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions. Unre …

Learning Invariants through Soft Unification. Collapsed amortized variational inference for switching nonlinear dynamical systems. Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. Target-Embedding Autoencoders for Supervised Representation Learning. COMBINED FLEXIBLE ACTIVATION FUNCTIONS FOR DEEP NEURAL NETWORKS. Neural M …

Neural networks with motivation. Unsupervised Disentanglement of Pose, Appearance and Background from Images and Videos. Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video. The Logical Expressiveness of Graph Neural Networks. Iterative energy-based projection on a normal data manifold for anomaly localization. Size-f …

PROGRESSIVE LEARNING AND DISENTANGLEMENT OF HIERARCHICAL REPRESENTATIONS. Learning transport cost from subset correspondence. On Robustness of Neural Ordinary Differential Equations. Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?. Sign Bits Are All You Need for Black-Box Attacks. Biologically inspired sleep algorithm for inc …

Training binary neural networks with real-to-binary convolutions. FALCON: Fast and Lightweight Convolution for Compressing and Accelerating CNN. Ridge Regression: Structure, Cross-Validation, and Sketching. Confidence Scores Make Instance-dependent Label-noise Learning Possible. FreeLB: Enhanced Adversarial Training for Language Understanding. Mode …