Search Results for author: Anish Khazane

Found 7 papers, 0 papers with code

Taxonomic Recommendations of Real Estate Properties with Textual Attribute Information

no code implementations27 Oct 2022 Zachary Harrison, Anish Khazane

In this extended abstract, we present an end to end approach for building a taxonomy of home attribute terms that enables hierarchical recommendations of real estate properties.

Attribute

DeepDefacer: Automatic Removal of Facial Features via U-Net Image Segmentation

no code implementations31 May 2022 Anish Khazane, Julien Hoachuck, Krzysztof J. Gorgolewski, Russell A. Poldrack

In this paper, we introduce DeepDefacer, an application of deep learning to MRI anonymization that uses a streamlined 3D U-Net network to mask facial regions in MRI images with a significant increase in speed over traditional de-identification software.

De-identification Image Segmentation +1

DeepTrax: Embedding Graphs of Financial Transactions

no code implementations16 Jul 2019 C. Bayan Bruss, Anish Khazane, Jonathan Rider, Richard Serpe, Antonia Gogoglou, Keegan E. Hines

In this paper, we present a novel application of representation learning to bipartite graphs of credit card transactions in order to learn embeddings of account and merchant entities.

BIG-bench Machine Learning Fraud Detection +4

Graph Embeddings at Scale

no code implementations3 Jul 2019 C. Bayan Bruss, Anish Khazane, Jonathan Rider, Richard Serpe, Saurabh Nagrecha, Keegan E. Hines

Graph embedding is a popular algorithmic approach for creating vector representations for individual vertices in networks.

Graph Embedding graph partitioning +1

An Adversarial Learning Framework For A Persona-Based Multi-Turn Dialogue Model

no code implementations NAACL 2019 Oluwatobi Olabiyi, Anish Khazane, Alan Salimov, Erik T. Mueller

In this paper, we extend the persona-based sequence-to-sequence (Seq2Seq) neural network conversation model to a multi-turn dialogue scenario by modifying the state-of-the-art hredGAN architecture to simultaneously capture utterance attributes such as speaker identity, dialogue topic, speaker sentiments and so on.

Attribute

A Persona-based Multi-turn Conversation Model in an Adversarial Learning Framework

no code implementations29 Apr 2019 Oluwatobi O. Olabiyi, Anish Khazane, Erik T. Mueller

In this paper, we extend the persona-based sequence-to-sequence (Seq2Seq) neural network conversation model to multi-turn dialogue by modifying the state-of-the-art hredGAN architecture.

Decoder

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