Contrastive learning-based methods, such as unsup-SimCSE, have achieved state-of-the-art (SOTA) performances in learning unsupervised sentence embeddings. However, previous studies, each embedding used for contrastive only derived from one instance, and we call these embeddings instance-level In other words, is regarded a unique class of its own, which may hurt the generalization performance. t...

We introduce a graphical framework for multiple instance learning (MIL) based on Markov networks. This framework can be used to model the traditional MIL definition as well as more general MIL definitions. Different levels of ambiguity – the portion of positive instances in a bag – can be explored in weakly supervised data. To train these models, we propose a discriminative maxmargin learning a...

Multiple-Instance Learning via Embedded Instance Selection (MILES) is a recently proposed multiple-instance (MI) classification algorithm that applies a single-instance base learner to a propositionalized version of MI data. However, the original authors consider only one single-instance base learner for the algorithm — the 1-norm SVM. We present an empirical study investigating the efficacy of...

Using a unique individual level data on the membership of Rotating Savings and Credit Associations (ROSCAs) collected in 1994 from seven major urban centres in Ethiopia, we provide one of the few econometric tests of the economic theory of ROSCAs. In recognition of the heterogeneity of rosca types across space, we provide basic information about the characteristics of roscas in urban areas of E...

Automatic screening of Age-related Macular Degeneration (AMD) is important for both patients and ophthalmologists. The major sign of contracting AMD at the early stage is the appearance of drusen, which are the accumulation of extracellular material and appear as yellow-white spots on the retina. In this paper, we propose an effective approach for drusen segmentation towards AMD screening. The ...

Human perception is capable of integrating local events to generate an overall impression at the global level; this is evident in daily life and is utilized repeatedly in behavioral science studies to bring objective measures into studies of human behavior. In this work, we explore two hypotheses considering whether it is the isolated-saliency or the causal-integration of information that can t...

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