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Found 10 papers, 1 papers with code
Hybrid Classification-Regression Adaptive Loss for Dense Object Detection
For object detection detectors, enhancing model performance hinges on the ability to simultaneously consider inconsistencies across tasks and focus on difficult-to-train samples.
Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure
Cancer treatments are known to introduce cardiotoxicity, negatively impacting outcomes and survivorship.
FreeStyle: Free Lunch for Text-guided Style Transfer using Diffusion Models
In the decoder, we further modulate features from the dual streams based on a given content image and the corresponding style text prompt for precise style transfer.
On Regularized Sparse Logistic Regression
Sparse logistic regression is for classification and feature selection simultaneously.
Strictly Low Rank Constraint Optimization -- An Asymptotically $\mathcal{O}(\frac{1}{t^2})$ Method
We study a class of non-convex and non-smooth problems with \textit{rank} regularization to promote sparsity in optimal solution.
Multi-Task Learning with Prior Information
Multi-task learning aims to boost the generalization performance of multiple related tasks simultaneously by leveraging information contained in those tasks.
Rethinking Symmetric Matrix Factorization: A More General and Better Clustering Perspective
Nonnegative matrix factorization (NMF) is widely used for clustering with strong interpretability.
DPOAD: Differentially Private Outsourcing of Anomaly Detection through Iterative Sensitivity Learning
Outsourcing anomaly detection to third-parties can allow data owners to overcome resource constraints (e. g., in lightweight IoT devices), facilitate collaborative analysis (e. g., under distributed or multi-party scenarios), and benefit from lower costs and specialized expertise (e. g., of Managed Security Service Providers).
Enriched Robust Multi-View Kernel Subspace Clustering
To address the above issues, in this paper we propose a novel Enriched Robust Multi-View Kernel Subspace Clustering framework where the consensus affinity matrix is learned from both multi-view data and spectral clustering.
Free resolutions of function classes via order complexes
Function classes are collections of Boolean functions on a finite set, which are fundamental objects of study in theoretical computer science.
