In this paper, we consider the problem of differentially private learning where access to the training features is through a kernel function only. As mentioned in Chaudhuri et al. (2011), the problem seems to be intractable for general kernel functions in the standard learning model of releasing different private predictor. We study this problem in three simpler but practical settings. We first...

In this paper we describe our approach for the MediaEval’s “Emotion in Music” task. Our method consists of deep Long-Short Term Memory Recurrent Neural Networks (LSTM-RNN) for dynamic Arousal and Valence regression, using acoustic and psychoacoustic features extracted from the songs that have been previously proven as effective for emotion prediction in music. Results on the challenge test demo...

Intelligibility predictors tell us a great deal about human speech perception, in particular which acoustic factors strongly effect human behavior, and which do not. A particular intelligibility predictor, the Articulation Index (AI), is interesting because it models human behavior in noise, and its form has implications about representation of speech in the brain. Specifically, the Articulatio...

Non-standard language as it appears in user-generated content has recently attracted much attention. This paper proposes that non-standardness comes in two basic varieties, technical and linguistic, and develops a machine-learning method to discriminate between standard and nonstandard texts in these two dimensions. We describe the manual annotation of a dataset of Slovene user-generated conten...

Determination of binding affinity of proteins in the formation of protein complexes requires sophisticated, expensive and time-consuming experimentation which can be replaced with computational methods. Most computational prediction techniques require protein structures which limit their applicability to protein complexes with known structures. In this work, we explore sequence based protein bi...

The main problem with localized discriminant techniques is the curse of dimensionality, which seems to restrict their use to the case of few variables. This restriction does not hold if localization is combined with a reduction of dimension. In particular it is shown that localization yields powerful classifiers even in higher dimensions if localization is combined with locally adaptive selecti...

Before providing the proof details, let us first describe the high-level intuition of our construction. Roughly speaking, oneshot averaging works well when the bias of the predictor returned by each machine (as a random vector in Euclidean space, based on the sampled training data) is much smaller than the variance. Since each such predictor is based on independent data, averaging m such predic...

Chronotropic incompetence (CI), broadly defined as the inability of the heart to increase its rate commensurate with increased activity or demand, is common in patients with cardiovascular disease, produces exercise intolerance that impairs quality of life, and is an independent predictor of major adverse cardiovascular events and overall mortality. However, the importance of CI is underappreci...

The aim of this study was to examine the relationship between personality dimensions (introversionextroversion) and Self-assertiveness with Social Anxiety among university students. The Sample consisted of 360 individuals (180 girls, 180 boys), selected by Moregan table. The tools of the research consisted of three questionnaires: Eysenck personality questionnaire, Self-assertiveness questionna...

Universal schema builds a knowledge base (KB) of entities and relations by jointly embedding all relation types from input KBs as well as textual patterns observed in raw text. In most previous applications of universal schema, each textual pattern is represented as a single embedding, preventing generalization to unseen patterns. Recent work employs a neural network to capture patterns’ compos...