We study the problem of efficiently predicting a correct program from a large set of programs induced from few input-output examples in Programming-byExample (PBE) systems. This is an important problem for making PBE systems usable so that users do not need to provide too many examples to learn the desired program. We first formalize the two classes of sharing that occurs in version-space algeb...

We present a novel system that helps nonexperts find sets of similar words. The user begins by specifying one or more seed words. The system then iteratively suggests a series of candidate words, which the user can either accept or reject. Current techniques for this task typically bootstrap a classifier based on a fixed seed set. In contrast, our system involves the user throughout the labelin...

This manuscript provides a brief overview of trends and developments in the area of Content-Based Audio Indexing and Retrieval (CBAIR), during the past few years. Here we explored some limitations and constrains of existing Query By Example (QBE) and Query By Humming (QBH) CBAIR systems. We talked about different methods to represent musical objects, like feature-based representation, musical p...

We show the existing solution of Poisson-Boltzmann equation (PBE) to violate charge conservation principle, and then derive the correct formula for charge density distribution (ρe) in a fluid. We replaced unphysical old boundary conditions with some conditions that have never been used. Our result demonstrates that PBE cannot explain the formation of ‘Electric Double Layer’ (EDL); it follows th...

We address the problem of learning comprehensive syntactic profiles for a set of strings. Real-world datasets, typically curated from multiple sources, often contain data in various formats. Thus any data processing task is preceded by the critical step of data format identification. However, manual inspection of data to identify various formats is infeasible in standard big-data scenarios. We ...

The use of community detection algorithms is explored within the framework of cover song identification, i.e. the automatic detection of different audio renditions of the same underlying musical piece. Until now, this task has been posed as a typical query-by-example task, where one submits a query song and the system retrieves a list of possible matches ranked by their similarity to the query....