Multi-class Classification
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Benchmarks
Most implemented
SentEval: An Evaluation Toolkit for Universal Sentence Representations
Evidential Deep Learning to Quantify Classification Uncertainty
Multimodal Speech Emotion Recognition and Ambiguity Resolution
Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification
Efficient Set-Valued Prediction in Multi-Class Classification
Efficient Deep Learning for Stereo Matching
Papers
A Structured State Space Sequence Model for Multi-Class Classification of Malware
By 2030, Internet of Things (IoT) devices are projected to reach 40 billion, with fast-paced technological advancements in fields such as industry, healthcare, agriculture, automobiles, and building/home automation syste…
Multi-class ClassificationMalware DetectionMulti-label versus multi-class classification of blood cells and their aggregates in microfluidic channels
Deformability cytometry (DC) is a type of imaging flow cytometry, which uses a camera-equipped device to measure cellular stiffness in addition to other cellular properties at high throughput. Cellular properties such as…
Multi-class ClassificationFairness in multi-class multi-group classification problems via contextial coherent risk measures
We propose a new design of fair classifiers for multi-class classification problems in the presence of vector-valued sensitive attributes. In that scenario each sensitive attribute has multiple values and forms several g…
Multi-class ClassificationOn the Structure of Address in Multi-Party Dialogue: From Discrete Labels to Continuous Levels
In multi-party dialogues between a dialogue system and multiple users, identifying to whom an utterance is addressed is a key challenge. Prior work has typically treated addressee detection as a multi-class classificatio…
Multi-class ClassificationWhen does distribution shift break graph neural networks calibration?
Graph neural networks (GNNs) are increasingly deployed in real-world applications where distribution shift is un-avoidable. However, how such shifts affect model calibration, defined as the agreement between predictive c…
Multi-class ClassificationA Multi-cluster Boundary Learning Method for Out-of-Scope Intent Detection via MiniLM Embedding
Intent detection is a critical task that bridges human intents and system actions in human-machine interaction systems. However, there still exist challenges for detecting out-of-scope (OOS) intents. (i) The traditional …
Multi-class ClassificationIntent Detection