Self-guided Approximate Linear Programs. Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data. Improved Techniques for Training Single-Image GANs. A C Code Generator for Fast Inference and Simple Deployment of Convolutional Neural Networks on Resource Constrained Systems. Image Fine-grained …

Challenges in Supporting Exploratory Search through Voice Assistants. Interpretability of Blackbox Machine Learning Models through Dataview Extraction and Shadow Model creation. Unsupervised Pre-trained, Texture Aware And Lightweight Model for Deep Learning-Based Iris Recognition Under Limited Annotated Data. Deep Learning for Automatic Tracking of …

DuDoNet++: Encoding mask projection to reduce CT metal artifacts. Saliency Enhancement using Gradient Domain Edges Merging. DNN-based Localization from Channel Estimates: Feature Design and Experimental Results. Domain Embedded Multi-model Generative Adversarial Networks for Image-based Face Inpainting. Learning to simulate and design for structura …

K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters. Compact Deep Aggregation for Set Retrieval. Manifold-based Test Generation for Image Classifiers. Superpixel Image Classification with Graph Attention Networks. High-dimensional, multiscale online changepoint detection. Theoretical Analysis of Divide-and-Conquer ERM: Beyond Square …

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 …