Search Results for author: Vivek Kulkarni

Found 31 papers, 10 papers with code

CTM -- A Model for Large-Scale Multi-View Tweet Topic Classification

no code implementations3 May 2022 Vivek Kulkarni, Kenny Leung, Aria Haghighi

In contrast to most prior work which only focuses on post classification into a small number of topics ($10$-$20$), we consider the task of large-scale topic classification in the context of Twitter where the topic space is $10$ times larger with potentially multiple topic associations per Tweet.

Classification Topic Classification

LMSOC: An Approach for Socially Sensitive Pretraining

1 code implementation Findings (EMNLP) 2021 Vivek Kulkarni, Shubhanshu Mishra, Aria Haghighi

Although language depends heavily on the geographical, temporal, and other social contexts of the speaker, these elements have not been incorporated into modern transformer-based language models.

Cloze Test Graph Representation Learning +2

Learning, Computing, and Trustworthiness in Intelligent IoT Environments: Performance-Energy Tradeoffs

no code implementations4 Oct 2021 Beatriz Soret, Lam D. Nguyen, Jan Seeger, Arne Bröring, Chaouki Ben Issaid, Sumudu Samarakoon, Anis El Gabli, Vivek Kulkarni, Mehdi Bennis, Petar Popovski

An Intelligent IoT Environment (iIoTe) is comprised of heterogeneous devices that can collaboratively execute semi-autonomous IoT applications, examples of which include highly automated manufacturing cells or autonomously interacting harvesting machines.

Edge-computing Total Energy

DialectGram: Detecting Dialectal Variation at Multiple Geographic Resolutions

1 code implementation4 Oct 2019 Hang Jiang, Haoshen Hong, Yuxing Chen, Vivek Kulkarni

In this work, we propose a model that enables detection of dialectal variation at multiple levels of geographic resolution obviating the need for a-priori definition of the resolution level.

Word Embeddings

What Should I Ask? Using Conversationally Informative Rewards for Goal-Oriented Visual Dialog

no code implementations28 Jul 2019 Pushkar Shukla, Carlos Elmadjian, Richika Sharan, Vivek Kulkarni, Matthew Turk, William Yang Wang

In this work, we focus on the task of goal-oriented visual dialogue, aiming to automatically generate a series of questions about an image with a single objective.

Visual Dialog

TWEETQA: A Social Media Focused Question Answering Dataset

no code implementations ACL 2019 Wenhan Xiong, Jiawei Wu, Hong Wang, Vivek Kulkarni, Mo Yu, Shiyu Chang, Xiaoxiao Guo, William Yang Wang

With social media becoming increasingly pop-ular on which lots of news and real-time eventsare reported, developing automated questionanswering systems is critical to the effective-ness of many applications that rely on real-time knowledge.

Question Answering

What Should I Ask? Using Conversationally Informative Rewards for Goal-oriented Visual Dialog.

no code implementations ACL 2019 Pushkar Shukla, Carlos Elmadjian, Richika Sharan, Vivek Kulkarni, Matthew Turk, William Yang Wang

In this work, we focus on the task of goal-oriented visual dialogue, aiming to automatically generate a series of questions about an image with a single objective.

Visual Dialog

MOHONE: Modeling Higher Order Network Effects in KnowledgeGraphs via Network Infused Embeddings

no code implementations1 Nov 2018 Hao Yu, Vivek Kulkarni, William Wang

First, we introduce methods that learn network representations of entities in the knowledge graph capturing these varied aspects of similarity.

Knowledge Graph Embedding Knowledge Graph Embeddings +2

DOLORES: Deep Contextualized Knowledge Graph Embeddings

no code implementations AKBC 2020 Haoyu Wang, Vivek Kulkarni, William Yang Wang

We introduce a new method DOLORES for learning knowledge graph embeddings that effectively captures contextual cues and dependencies among entities and relations.

Knowledge Graph Embeddings Knowledge Graphs +2

Simple Models for Word Formation in Slang

1 code implementation NAACL 2018 Vivek Kulkarni, William Yang Wang

We propose the first generative models for three types of extra-grammatical word formation phenomena abounding in slang: Blends, Clippings, and Reduplicatives.

Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media

2 code implementations11 Apr 2018 Mai ElSherief, Vivek Kulkarni, Dana Nguyen, William Yang Wang, Elizabeth Belding

While social media empowers freedom of expression and individual voices, it also enables anti-social behavior, online harassment, cyberbullying, and hate speech.

Simple Models for Word Formation in English Slang

1 code implementation7 Apr 2018 Vivek Kulkarni, William Yang Wang

We propose generative models for three types of extra-grammatical word formation phenomena abounding in English slang: Blends, Clippings, and Reduplicatives.

TFW, DamnGina, Juvie, and Hotsie-Totsie: On the Linguistic and Social Aspects of Internet Slang

no code implementations22 Dec 2017 Vivek Kulkarni, William Yang Wang

In this work, we use UrbanDictionary to conduct the first large-scale linguistic analysis of slang and its social aspects on the Internet to yield insights into this variety of language that is increasingly used all over the world online.

Question Answering

Human Centered NLP with User-Factor Adaptation

no code implementations EMNLP 2017 Veronica Lynn, Youngseo Son, Vivek Kulkarni, Niranjan Balasubramanian, H. Andrew Schwartz

We pose the general task of user-factor adaptation {--} adapting supervised learning models to real-valued user factors inferred from a background of their language, reflecting the idea that a piece of text should be understood within the context of the user that wrote it.

Document Classification Domain Adaptation +4

Latent Human Traits in the Language of Social Media: An Open-Vocabulary Approach

no code implementations22 May 2017 Vivek Kulkarni, Margaret L. Kern, David Stillwell, Michal Kosinski, Sandra Matz, Lyle Ungar, Steven Skiena, H. Andrew Schwartz

Taking advantage of linguistic information available through Facebook, we study the process of inferring a new set of potential human traits based on unprompted language use.

Domain Adaptation for Named Entity Recognition in Online Media with Word Embeddings

no code implementations1 Dec 2016 Vivek Kulkarni, Yashar Mehdad, Troy Chevalier

In this paper, we propose methods to effectively adapt models learned on one domain onto other domains using distributed word representations.

Domain Adaptation Named Entity Recognition +2

Data Centroid Based Multi-Level Fuzzy Min-Max Neural Network

no code implementations19 Aug 2016 Shraddha Deshmukh, Sagar Gandhi, Pratap Sanap, Vivek Kulkarni

In this brief, an extension of MLF is proposed which defines a new boundary region, where the previously proposed methods mark decisions with less confidence and hence misclassification is more frequent.

General Classification

On the Convergent Properties of Word Embedding Methods

no code implementations12 May 2016 Yingtao Tian, Vivek Kulkarni, Bryan Perozzi, Steven Skiena

Do word embeddings converge to learn similar things over different initializations?

Word Embeddings

Theano: A Python framework for fast computation of mathematical expressions

1 code implementation9 May 2016 The Theano Development Team, Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermueller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre-Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Mélanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian Goodfellow, Matt Graham, Caglar Gulcehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrancois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert T. McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements.

Dimensionality Reduction General Classification

Don't Walk, Skip! Online Learning of Multi-scale Network Embeddings

2 code implementations6 May 2016 Bryan Perozzi, Vivek Kulkarni, Haochen Chen, Steven Skiena

We present Walklets, a novel approach for learning multiscale representations of vertices in a network.

Social and Information Networks Physics and Society

Freshman or Fresher? Quantifying the Geographic Variation of Internet Language

2 code implementations22 Oct 2015 Vivek Kulkarni, Bryan Perozzi, Steven Skiena

Our analysis of British and American English over a period of 100 years reveals that semantic variation between these dialects is shrinking.

To Drop or Not to Drop: Robustness, Consistency and Differential Privacy Properties of Dropout

no code implementations6 Mar 2015 Prateek Jain, Vivek Kulkarni, Abhradeep Thakurta, Oliver Williams

Moreover, using the above mentioned stability properties of dropout, we design dropout based differentially private algorithms for solving ERMs.

L2 Regularization

Statistically Significant Detection of Linguistic Change

no code implementations12 Nov 2014 Vivek Kulkarni, Rami Al-Rfou, Bryan Perozzi, Steven Skiena

We propose a new computational approach for tracking and detecting statistically significant linguistic shifts in the meaning and usage of words.

Change Point Detection Time Series

POLYGLOT-NER: Massive Multilingual Named Entity Recognition

no code implementations14 Oct 2014 Rami Al-Rfou, Vivek Kulkarni, Bryan Perozzi, Steven Skiena

We describe a system that builds Named Entity Recognition (NER) annotators for 40 major languages using Wikipedia and Freebase.

Information Retrieval Machine Translation +4

Exploring the power of GPU's for training Polyglot language models

no code implementations5 Apr 2014 Vivek Kulkarni, Rami Al-Rfou', Bryan Perozzi, Steven Skiena

We evaluate the performance of training the model on the GPU and present optimizations that boost the performance on the GPU. One of the key optimizations, we propose increases the performance of a function involved in calculating and updating the gradient by approximately 50 times on the GPU for sufficiently large batch sizes.

Inducing Language Networks from Continuous Space Word Representations

no code implementations6 Mar 2014 Bryan Perozzi, Rami Al-Rfou, Vivek Kulkarni, Steven Skiena

Recent advancements in unsupervised feature learning have developed powerful latent representations of words.

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