research
∙
08/28/2023
Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond
Visual similarities discovery (VSD) is an important task with broad e-co...
share
research
∙
06/28/2023
Representation Learning via Variational Bayesian Networks
We present Variational Bayesian Network (VBN) - a novel Bayesian entity ...
research
∙
06/09/2023
GPT-Calls: Enhancing Call Segmentation and Tagging by Generating Synthetic Conversations via Large Language Models
Transcriptions of phone calls are of significant value across diverse fi...
research
∙
08/13/2022
Interpreting BERT-based Text Similarity via Activation and Saliency Maps
Recently, there has been growing interest in the ability of Transformer-...
research
∙
08/13/2022
MetricBERT: Text Representation Learning via Self-Supervised Triplet Training
We present MetricBERT, a BERT-based model that learns to embed text unde...
research
∙
04/23/2022
Grad-SAM: Explaining Transformers via Gradient Self-Attention Maps
Transformer-based language models significantly advanced the state-of-th...
research
∙
12/12/2021
Cold Item Integration in Deep Hybrid Recommenders via Tunable Stochastic Gates
A major challenge in collaborative filtering methods is how to produce r...
research
∙
09/02/2021
GAM: Explainable Visual Similarity and Classification via Gradient Activation Maps
We present Gradient Activation Maps (GAM) - a machinery for explaining p...
research
∙
06/02/2021
Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference
We present a novel model for the problem of ranking a collection of docu...
research
∙
09/26/2020
Explainable Recommendations via Attentive Multi-Persona Collaborative Filtering
Two main challenges in recommender systems are modeling users with heter...
research
∙
09/25/2020
RecoBERT: A Catalog Language Model for Text-Based Recommendations
Language models that utilize extensive self-supervised pre-training from...
research
∙
04/12/2020
Bayesian Hierarchical Words Representation Learning
This paper presents the Bayesian Hierarchical Words Representation (BHWR...
research
∙
02/18/2020
Neural Attentive Multiview Machines
An important problem in multiview representation learning is finding the...
research
∙
02/15/2020
Attentive Item2Vec: Neural Attentive User Representations
Factorization methods for recommender systems tend to represent users as...
research
∙
12/03/2019
Multiscale Self Attentive Convolutions for Vision and Language Modeling
Self attention mechanisms have become a key building block in many state...
research
∙
08/14/2019
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding
Attention based models have become the new state-of-the-art in natural l...
research
∙
12/15/2018
Deep Synthesizer Parameter Estimation
Sound synthesis is a complex field that requires domain expertise. Manua...
research
∙
12/22/2017
Predicting Relevance Scores for Triples from Type-Like Relations using Neural Embedding - The Cabbage Triple Scorer at WSDM Cup 2017
The WSDM Cup 2017 Triple scoring challenge is aimed at calculating and a...
research
∙
11/01/2016
The Deep Journey from Content to Collaborative Filtering
In Recommender Systems research, algorithms are often characterized as e...
research
∙
03/21/2016
Bayesian Neural Word Embedding
Recently, several works in the domain of natural language processing pre...
research
∙
03/14/2016
Item2Vec: Neural Item Embedding for Collaborative Filtering
Many Collaborative Filtering (CF) algorithms are item-based in the sense...
research
∙
03/07/2016