Hopfield networks is all you need
We introduce a modern Hopfield network with continuous states and a corresponding
update rule. The new Hopfield network can store exponentially (with the dimension of the …
update rule. The new Hopfield network can store exponentially (with the dimension of the …
Chemical complexity challenge: Is multi‐instance machine learning a solution?
Molecules are complex dynamic objects that can exist in different molecular forms
(conformations, tautomers, stereoisomers, protonation states, etc.) and often it is not known …
(conformations, tautomers, stereoisomers, protonation states, etc.) and often it is not known …
Multiple instance learning: A survey of problem characteristics and applications
Multiple instance learning (MIL) is a form of weakly supervised learning where training
instances are arranged in sets, called bags, and a label is provided for the entire bag. This …
instances are arranged in sets, called bags, and a label is provided for the entire bag. This …
A comprehensive review on multiple instance learning
Multiple-instance learning has become popular over recent years due to its use in some
special scenarios. It is basically a type of weakly supervised learning where the learning …
special scenarios. It is basically a type of weakly supervised learning where the learning …
Robust bag classification approach for multi-instance learning via subspace fuzzy clustering
Multi-instance learning (MIL) allows predictive algorithms to use complex data
representation. The data in MIL is organized in the form of labeled bags of instances, and …
representation. The data in MIL is organized in the form of labeled bags of instances, and …
Palmprint recognition with an efficient data driven ensemble classifier
Palmprint recognition is an important and widely used modality in biometric systems. It has a
high reliability, stability and user acceptability. This paper proposes a new and effective …
high reliability, stability and user acceptability. This paper proposes a new and effective …
Double similarities weighted multi-instance learning kernel and its application
Abstract Multi-instance learning (MIL), as a special version of classification, focuses on
labeled sets (bags) consisting of unlabeled instances and has drawn accumulative attention …
labeled sets (bags) consisting of unlabeled instances and has drawn accumulative attention …
A selective multiple instance transfer learning method for text categorization problems
B Liu, Y **ao, Z Hao - Knowledge-Based Systems, 2018 - Elsevier
Multiple instance learning (MIL) is a generalization of supervised learning which attempts to
learn a distinctive classifier from bags of instances. This paper addresses the problem of the …
learn a distinctive classifier from bags of instances. This paper addresses the problem of the …
Deep Gaussian mixture model based instance relevance estimation for multiple instance learning applications
Multiple instance learning (MIL) is a type of supervised learning, where instead of receiving
a collection of individually labeled examples, the learner is given weakly labeled bags of …
a collection of individually labeled examples, the learner is given weakly labeled bags of …
Simultaneous instance pooling and bag representation selection approach for multiple-instance learning (MIL) using vision transformer
In multiple-instance learning (MIL), the existing bag encoding and attention-based pooling
approaches assume that the instances in the bag have no relationship among them. This …
approaches assume that the instances in the bag have no relationship among them. This …