Deep Learning Task

Deep learning research focuses on developing and improving neural network models for various tasks, aiming to enhance accuracy, efficiency, and robustness. Current efforts concentrate on optimizing model architectures (like transformers and convolutional networks), improving training methods (including novel optimization algorithms and learning rate tuning), and addressing challenges such as data scarcity, heterogeneity, and privacy concerns through techniques like iterative refinement and privacy-preserving collaborative inference. These advancements have significant implications for diverse applications across computer vision, natural language processing, medical imaging, and beyond, driving progress in both scientific understanding and practical deployment of AI systems.

Papers

November 7, 2024

Classification with Conceptual Safeguards
Hailey Joren, Charles Marx, Berk Ustun
Classification Code Deep Learning Task Concept Prediction Semantic Constraint

July 29, 2024

Octave-YOLO: Cross frequency detection network with octave convolution
Sangjune Shin, Dongkun Shin
Real Time Object Convolutional Neural Network Architecture Spatial Frequency Deep Learning Task Variational Bottleneck

April 8, 2024

Iterative Refinement Strategy for Automated Data Labeling: Facial Landmark Diagnosis in Medical Imaging
Yu-Hsi Chen
Medical Imaging Iterative Refinement Facial Landmark Data Labeling Labeling Technique Deep Learning Task

October 15, 2023

Score-Based Methods for Discrete Optimization in Deep Learning
Eric Lei, Arman Adibi, Hamed Hassani
Deep Learning Score Based Discrete Optimization Deep Learning Task Discrete Optimization Problem

September 6, 2023

Roulette: A Semantic Privacy-Preserving Device-Edge Collaborative Inference Framework for Deep Learning Classification Tasks
Jingyi Li, Guocheng Liao, Lin Chen, Xu Chen
Ground Truth Differential Privacy Guarantee Collaborative Inference Deep Learning Task Privacy Preserving Inference

June 11, 2023

A Comprehensive Survey on Applications of Transformers for Deep Learning Tasks
Saidul Islam, Hanae Elmekki, Ahmed Elsebai, Jamal Bentahar, Najat Drawel, Gaith Rjoub, Witold Pedrycz
Transformer Megatron Decepticons Transformer Based Financial Application Long Short Term Memory Transformer Model Transformer Based Model Comprehensive Survey Deep Learning Task

June 4, 2023

Multi-Predict: Few Shot Predictors For Efficient Neural Architecture Search
Yash Akhauri, Mohamed S. Abdelfattah
Neural Architecture Search Deep Learning Task Hardware Aware Neural Architecture Search Latency Predictor

May 31, 2023

Mechanic: A Learning Rate Tuner
Ashok Cutkosky, Aaron Defazio, Harsh Mehta
Learning Rate Online Convex Optimization Deep Learning Task Mechanical Engineering Base Algorithm

March 6, 2023

Judging Adam: Studying the Performance of Optimization Methods on ML4SE Tasks
Dmitry Pasechnyuk, Anton Prazdnichnykh, Mikhail Evtikhiev, Timofey Bryksin
System Performance Optimization Method Better Optimizers Deep Learning Task

February 19, 2023

Optimization Methods in Deep Learning: A Comprehensive Overview
David Shulman
Deep Learning Deep Neural Network Stochastic Gradient Descent First Order Optimization Method Deep Learning Task

February 9, 2023

The Re-Label Method For Data-Centric Machine Learning
Tong Guo
Data Centric Noisy Data Deep Learning Application Deep Learning Task Sequence Tagging Human Labeling

November 28, 2022

Pitfalls of Conditional Batch Normalization for Contextual Multi-Modal Learning
Ivaxi Sheth, Aamer Abdul Rahman, Mohammad Havaei, Samira Ebrahimi Kahou
Convolutional Neural Network Strong Generalization Natural Image Batch Normalization Common Pitfall Multimodal in Context Learning Deep Learning Task

October 5, 2022

Goal Recognition as a Deep Learning Task: the GRNet Approach
Mattia Chiari, Alfonso E. Gerevini, Luca Putelli, Francesco Percassi, Ivan Serina
GNN Based Planning Domain Deep Learning Task Goal Recognition Joint Goal Accuracy

August 3, 2022

Maintaining Performance with Less Data
Dominic Sanderson, Tatiana Kalgonova
Image Classification System Performance Neural Network Model Data Reduction Deep Learning Task Less Data

May 4, 2022

Convolutional and Residual Networks Provably Contain Lottery Tickets
Rebekka Burkholz
Deep Neural Network Deep Convolutional Neural Network Activation Function Residual Network ReLU Activation Lottery Ticket Hypothesis Deep Learning Task

February 20, 2022

On Optimal Early Stopping: Over-informative versus Under-informative Parametrization
Ruoqi Shen, Liyao Gao, Yi-An Ma
Deep Neural Network Early Stopping Output Space Deep Learning Task

February 10, 2022

A Field of Experts Prior for Adapting Neural Networks at Test Time
Neerav Karani, Georg Brunner, Ertunc Erdil, Simin Fei, Kerem Tezcan, Krishna Chaitanya, Ender Konukoglu
Neural Network Expert Knowledge Image Registration Test Time Limited Field Tissue Segmentation Deep Learning Task Magnetic Resonance Imaging Segmentation

January 28, 2022

Benchmarking Resource Usage for Efficient Distributed Deep Learning
Nathan C. Frey, Baolin Li, Joseph McDonald, Dan Zhao, Michael Jones, David Bestor, Devesh Tiwari, Vijay Gadepally, Siddharth Samsi
Deep Learning Deep Learning Model New Benchmark High Efficiency Deep Network Computational Resource Deep Learning Task

December 1, 2021

Compare Where It Matters: Using Layer-Wise Regularization To Improve Federated Learning on Heterogeneous Data
Ha Min Son, Moon Hyun Kim, Tai-Myoung Chung
Neural Network Consistent Comparison Heterogeneous Data Deep Learning Task Kernel Alignment Layer Regularization Centered Kernel Alignment

November 14, 2021

A layer-stress learning framework universally augments deep neural network tasks
Shihao Shao, Yong Liu, Qinghua Cui
Convolutional Neural Network Deep Neural Network Deep Network Hidden Layer Deep Learning Task Deep Learning Layer