1 citations · 2 across the 3 of their papers we have counts for
4 papers
QUIS: Question-guided Insights Generation for Automated Exploratory Data Analysis
Abhijit Manatkar, Ashlesha Akella, Parthivi Gupta +1
Discovering meaningful insights from a large dataset, known as Exploratory Data Analysis (EDA), is a challenging task that requires thorough exploration and analysis of the data. A…
Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach
Tao Yang, Cuize Han, Chen Luo +3
Ranking is at the core of many artificial intelligence (AI) applications, including search engines, recommender systems, etc. Modern ranking systems are often constructed with lear…
Analysis of E-commerce Ranking Signals via Signal Temporal Logic
Tommaso Dreossi, Giorgio Ballardin, Parth Gupta +3
The timed position of documents retrieved by learning to rank models can be seen as signals. Signals carry useful information such as drop or rise of documents over time or user be…
Squeezing bottlenecks: exploring the limits of autoencoder semantic representation capabilities
Parth Gupta, Rafael E. Banchs, Paolo Rosso
We present a comprehensive study on the use of autoencoders for modelling text data, in which (differently from previous studies) we focus our attention on the following issues: i)…