Papers
Wed 2 Feb 2022
151 papers
- Yordle: An Efficient Imitation Learning for Branch and BoundOffline RL and imitation learning from data → Imitation learning methods
- Causal Imitation Learning under Temporally Correlated NoiseOffline RL and imitation learning from data → Imitation learning methods
- Imitation Learning by Estimating Expertise of DemonstratorsOffline RL and imitation learning from data → Imitation learning methods
- Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership InferenceLLM safety and security → Membership inference attacks
- A Survey on Retrieval-Augmented Text GenerationRetrieval-augmented generation → RAG pipeline design and evaluation
- Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy TrafficEnd-to-end autonomous driving → Cooperative and V2X driving
- GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records
- Understanding The Robustness of Self-supervised Learning Through Topic Modeling
- Toward a traceable, explainable, and fairJD/Resume recommendation system
- Context-Aware Discrimination Detection in Job Vacancies using Computational Language Models
- Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning
- Integration of a machine learning model into a decision support tool to predict absenteeism at work of prospective employees
- Human Activity Recognition Using Tools of Convolutional Neural Networks: A State of the Art Review, Data Sets, Challenges and Future Prospects
- Spectro Temporal EEG Biomarkers For Binary Emotion Classification
- AI Research Associate for Early-Stage Scientific Discovery
- Proceedings 10th International Workshop on Theorem Proving Components for Educational Software
- Performance of multilabel machine learning models and risk stratification schemas for predicting stroke and bleeding risk in patients with non-valvular atrial fibrillation
- DeepQMLP: A Scalable Quantum-Classical Hybrid DeepNeural Network Architecture for Classification
- AtmoDist: Self-supervised Representation Learning for Atmospheric Dynamics
- Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation
- Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization
- Training a Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection
- Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions
- PanoDepth: A Two-Stage Approach for Monocular Omnidirectional Depth Estimation
- Deep Learning for Epidemiologists: An Introduction to Neural Networks
- Approximating Full Conformal Prediction at Scale via Influence Functions
- Gradient estimators for normalising flows
- Multi-Resolution Factor Graph Based Stereo Correspondence Algorithm
- Impact Analysis of Harassment Against Women Using Association Rule Mining Approaches: Bangladesh Prospective
- Harmony: Overcoming the Hurdles of GPU Memory Capacity to Train Massive DNN Models on Commodity Servers
- A Comparison of Online Hate on Reddit and 4chan: A Case Study of the 2020 US Election
- Causal Inference Through the Structural Causal Marginal Problem
- Improved Regret for Differentially Private Exploration in Linear MDP
- Cyclical Pruning for Sparse Neural Networks
- Fenrir: Physics-Enhanced Regression for Initial Value Problems
- ASR-Aware End-to-end Neural Diarization
- An Experience Report of Executive-Level Artificial Intelligence Education in the United Arab Emirates
- PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts
- Global Optimization Networks
- Topological Classification in a Wasserstein Distance Based Vector Space
- Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features
- Robust Estimation for Nonparametric Families via Generative Adversarial Networks
- DASHA: Distributed Nonconvex Optimization with Communication Compression, Optimal Oracle Complexity, and No Client Synchronization
- FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations
- Automated processing of X-ray computed tomography images via panoptic segmentation for modeling woven composite textiles
- NoisyMix: Boosting Model Robustness to Common Corruptions
- Efficient Memory Partitioning in Software Defined Hardware
- Accelerated Quality-Diversity through Massive Parallelism
- Speaker Normalization for Self-supervised Speech Emotion Recognition
- PolarDenseNet: A Deep Learning Model for CSI Feedback in MIMO Systems
- Approximate Bisimulation Relations for Neural Networks and Application to Assured Neural Network Compression
- Training Semantic Descriptors for Image-Based Localization
- VOS: Learning What You Don't Know by Virtual Outlier Synthesis
- Smoothed Embeddings for Certified Few-Shot Learning
- Heterogeneous manifolds for curvature-aware graph embedding
- Transfer in Reinforcement Learning via Regret Bounds for Learning Agents
- Make Some Noise: Reliable and Efficient Single-Step Adversarial Training
- Epidemic Dreams: Dreaming about health during the COVID-19 pandemic
- Unified Scaling Laws for Routed Language Models
- L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT Language Models, and Resources
- Error Correction in ASR using Sequence-to-Sequence Models
- The slurk Interaction Server Framework: Better Data for Better Dialog Models
- Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners
- Improving Screening Processes via Calibrated Subset Selection
- Relative Position Prediction as Pre-training for Text Encoders
- Pop Quiz! Can a Large Language Model Help With Reverse Engineering?
- Federated Reinforcement Learning for Collective Navigation of Robotic Swarms
- Surrogate Modeling for Physical Systems with Preserved Properties and Adjustable Tradeoffs
- Probabilistically Robust Learning: Balancing Average- and Worst-case Performance
- Structure-preserving GANs
- Language Models Explain Word Reading Times Better Than Empirical Predictability
- GLISp-r: A preference-based optimization algorithm with convergence guarantees
- An ASP approach for reasoning on neural networks under a finitely many-valued semantics for weighted conditional knowledge bases
- On Linear Separability under Linear Compression with Applications to Hard Support Vector Machine
- An Eye for an Eye: Defending against Gradient-based Attacks with Gradients
- An Optimal Transport Perspective on Unpaired Image Super-Resolution
- NeuRegenerate: A Framework for Visualizing Neurodegeneration
- Learning to reason about and to act on physical cascading events
- Keyword localisation in untranscribed speech using visually grounded speech models
- Identifying Suitable Tasks for Inductive Transfer Through the Analysis of Feature Attributions
- RescoreBERT: Discriminative Speech Recognition Rescoring with BERT
- Communication Efficient Federated Learning for Generalized Linear Bandits
- Giga-scale Kernel Matrix Vector Multiplication on GPU
- Interpretability for Multimodal Emotion Recognition using Concept Activation Vectors
- Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models, Benchmark and Efficient Evaluation
- Element selection for functional materials discovery by integrated machine learning of elemental contributions to properties
- Knowledge Engineering in the Long Game of Artificial Intelligence: The Case of Speech Acts
- Using Ballistocardiography for Sleep Stage Classification
- Detecting Privacy Requirements from User Stories with NLP Transfer Learning Models
- Diagnosing failures of fairness transfer across distribution shift in real-world medical settings
- MMSys'22 Grand Challenge on AI-based Video Production for Soccer
- MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-ray
- Multi-Task Learning as a Bargaining Game
- Fairness of Machine Learning Algorithms in Demography
- Auto-Transfer: Learning to Route Transferrable Representations
- 3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation
- Gradient Variance Loss for Structure-Enhanced Image Super-Resolution
- MD-GAN with multi-particle input: the machine learning of long-time molecular behavior from short-time MD data
- Normalise for Fairness: A Simple Normalisation Technique for Fairness in Regression Machine Learning Problems
- Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions
All 151
- Dictionary learning for clustering on hyperspectral images
- Posterior temperature optimized Bayesian models for inverse problems in medical imaging
- Robust Training of Neural Networks Using Scale Invariant Architectures
- VC-PCR: A Prediction Method based on Supervised Variable Selection and Clustering
- DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation
- Optimal high-dimensional and nonparametric distributed testing under communication constraints
- GANSlider: How Users Control Generative Models for Images using Multiple Sliders with and without Feedforward Information
- What Has Been Enhanced in my Knowledge-Enhanced Language Model?
- Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Prediction
- Asynchronous Decentralized Learning over Unreliable Wireless Networks
- Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters
- TONet: Tone-Octave Network for Singing Melody Extraction from Polyphonic Music
- Eikonal Fields for Refractive Novel-View Synthesis
- CTMSTOU driven markets: simulated environment for regime-awareness in trading policies
- Non-Stationary Dueling Bandits
- Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health
- Lipschitz-constrained Unsupervised Skill Discovery
- Invariant Ancestry Search
- Active Multi-Task Representation Learning
- CSFlow: Learning Optical Flow via Cross Strip Correlation for Autonomous Driving
- Image Forgery Detection with Interpretability
- Using Deep Learning to Bootstrap Abstractions for Hierarchical Robot Planning
- Retrieve-and-Fill for Scenario-based Task-Oriented Semantic Parsing
- Quantification and Aggregation over Concepts of the Ontology
- Methodology for forecasting and optimization in IEEE-CIS 3rd Technical Challenge
- Mold into a Graph: Efficient Bayesian Optimization over Mixed-Spaces
- Does Video Compression Impact Tracking Accuracy?
- Accurate calibration of multi-perspective cameras from a generalization of the hand-eye constraint
- Automotive Parts Assessment: Applying Real-time Instance-Segmentation Models to Identify Vehicle Parts
- MPVNN: Mutated Pathway Visible Neural Network Architecture for Interpretable Prediction of Cancer-specific Survival Risk
- Automated Detection of Doxing on Twitter
- A Longitudinal Dataset of Twitter ISIS Users
- A selective review of sufficient dimension reduction for multivariate response regression
- HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection
- Efficient Algorithms for Learning to Control Bandits with Unobserved Contexts
- Decoupled IoU Regression for Object Detection
- Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods
- The Role of Linear Layers in Nonlinear Interpolating Networks
- Extension: Adaptive Sampling with Implicit Radiance Field
- Active Audio-Visual Separation of Dynamic Sound Sources
- Some Reflections on Drawing Causal Inference using Textual Data: Parallels Between Human Subjects and Organized Texts
- Adaptive Experimentation with Delayed Binary Feedback
- Pose Guided Image Generation from Misaligned Sources via Residual Flow Based Correction
- Streaming Multi-Talker ASR with Token-Level Serialized Output Training
- Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks
- On-Sensor Binarized Fully Convolutional Neural Network with A Pixel Processor Array
- Nonlinear Initialization Methods for Low-Rank Neural Networks
- Co-training Improves Prompt-based Learning for Large Language Models
- KSD Aggregated Goodness-of-fit Test
- Optimizing Sequential Experimental Design with Deep Reinforcement Learning
- Do Differentiable Simulators Give Better Policy Gradients?