activity
20192021
most citedModel Adaptation via Model Interpolation and Boosting for Web Search Ranking

42 citations · 45 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL2021

Multi-Task Triplet Loss for Named Entity Recognition using Supplementary Text

Ryan Siskind, Shalin Shah

Retail item data contains many different forms of text like the title of an item, the description of an item, item name and reviews. It is of interest to identify the item name in…

cs.CL2021

Multi-Task Learning of Query Intent and Named Entities using Transfer Learning

Shalin Shah, Ryan Siskind

Named entity recognition (NER) has been studied extensively and the earlier algorithms were based on sequence labeling like Hidden Markov Models (HMM) and conditional random fields…

physics.ao-ph2020

Analysis of Greenhouse Gases

Shalin Shah

Climate change is a result of a complex system of interactions of greenhouse gases (GHG), the ocean, land, ice, and clouds. Large climate change models use several computers and so…

cs.LG2019

Hebbian Graph Embeddings

Shalin Shah, Venkataramana Kini

Representation learning has recently been successfully used to create vector representations of entities in language learning, recommender systems and in similarity learning. Graph…

cs.NE2019

Genetic Algorithm for the 0/1 Multidimensional Knapsack Problem

Shalin Shah

The 0/1 multidimensional knapsack problem is the 0/1 knapsack problem with m constraints which makes it difficult to solve using traditional methods like dynamic programming or bra…

cs.LG201942 cited

Model Adaptation via Model Interpolation and Boosting for Web Search Ranking

Jianfeng Gao, Qiang Wu, Chris Burges +5

This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The resu…