Search Results - "Gartrell, Mike"

Group-based Latent Dirichlet Allocation (Group-LDA): Effective audience detection for books in online social media by Zhang, Peng, Gu, Hansu, Gartrell, Mike, Lu, Tun, Yang, Dayi, Ding, Xianghua, Gu, Ning

“…Most current book recommendation and marketing strategies in online social media are implemented by creating topics or posting advertisements for the brand…”
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WhozThat? evolving an ecosystem for context-aware mobile social networks by Beach, A., Gartrell, M., Akkala, S., Elston, J., Kelley, J., Nishimoto, K., Ray, B., Razgulin, S., Sundaresan, K., Surendar, B., Terada, M., Han, R.

“…One of the most compelling social questions, which until now was left unanswered by current technology, is "Who's that?" This question is usually asked about a…”
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Learning from Multiple Sources for Data-to-Text and Text-to-Data by Duong, Song, Lumbreras, Alberto, Gartrell, Mike, Gallinari, Patrick

“…Data-to-text (D2T) and text-to-data (T2D) are dual tasks that convert structured data, such as graphs or tables into fluent text, and vice versa. These tasks…”
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Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes by Han, Insu, Gartrell, Mike, Dohmatob, Elvis, Karbasi, Amin

“…A determinantal point process (DPP) is an elegant model that assigns a probability to every subset of a collection of $n$ items. While conventionally a DPP is…”
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Differentially Private Gradient Flow based on the Sliced Wasserstein Distance by Sebag, Ilana, Pydi, Muni Sreenivas, Franceschi, Jean-Yves, Rakotomamonjy, Alain, Gartrell, Mike, Atif, Jamal, Allauzen, Alexandre

“…Safeguarding privacy in sensitive training data is paramount, particularly in the context of generative modeling. This can be achieved through either…”
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Scalable Sampling for Nonsymmetric Determinantal Point Processes by Han, Insu, Gartrell, Mike, Gillenwater, Jennifer, Dohmatob, Elvis, Karbasi, Amin

“…A determinantal point process (DPP) on a collection of $M$ items is a model, parameterized by a symmetric kernel matrix, that assigns a probability to every…”
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Embedding models for recommendation under contextual constraints by Krichene, Syrine, Gartrell, Mike, Calauzenes, Clement

“…Embedding models, which learn latent representations of users and items based on user-item interaction patterns, are a key component of recommendation systems…”
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Wasserstein Learning of Determinantal Point Processes by Anquetil, Lucas, Gartrell, Mike, Rakotomamonjy, Alain, Tanielian, Ugo, Calauzènes, Clément

“…Determinantal point processes (DPPs) have received significant attention as an elegant probabilistic model for discrete subset selection. Most prior work on…”
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Unifying GANs and Score-Based Diffusion as Generative Particle Models by Franceschi, Jean-Yves, Gartrell, Mike, Santos, Ludovic Dos, Issenhuth, Thibaut, de Bézenac, Emmanuel, Chen, Mickaël, Rakotomamonjy, Alain

“…Thirty-seventh Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, Dec. 2023, New Orleans, LA, USA…”
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Deep Determinantal Point Processes by Gartrell, Mike, Dohmatob, Elvis, Alberdi, Jon

“…Determinantal point processes (DPPs) have attracted significant attention as an elegant model that is able to capture the balance between quality and diversity…”
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Multi-Task Determinantal Point Processes for Recommendation by Warlop, Romain, Mary, Jérémie, Gartrell, Mike

“…Determinantal point processes (DPPs) have received significant attention in the recent years as an elegant model for a variety of machine learning tasks, due…”
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Adversarial Training of Word2Vec for Basket Completion by Tanielian, Ugo, Gartrell, Mike, Vasile, Flavian

“…In recent years, the Word2Vec model trained with the Negative Sampling loss function has shown state-of-the-art results in a number of machine learning tasks,…”
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WhozThat? Evolving an Ecosystem for Context-Aware Mobile Social Networks by Beach, Aaron, Gartrell, Mike, Akkala, Sirisha, Elston, Jack, Kelley, John, Nishimoto, Keisuke, Ray, Baishakhi, Razgulin, Sergei, Sundaresan, Karthik, Surendar, Bonnie, Terada, Michael, Han, Richard

“…One of the most compelling social questions, which until now was left unanswered by current technology, is "Who's that?" This question is usually asked about a…”
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Combining Reward and Rank Signals for Slate Recommendation by Aouali, Imad, Ivanov, Sergey, Gartrell, Mike, Rohde, David, Vasile, Flavian, Zaytsev, Victor, Legrand, Diego

“…We consider the problem of slate recommendation, where the recommender system presents a user with a collection or slate composed of K recommended items at…”
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Learning Determinantal Point Processes by Corrective Negative Sampling by Mariet, Zelda, Gartrell, Mike, Sra, Suvrit

“…Determinantal Point Processes (DPPs) have attracted significant interest from the machine-learning community due to their ability to elegantly and tractably…”
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Learning Nonsymmetric Determinantal Point Processes by Gartrell, Mike, Brunel, Victor-Emmanuel, Dohmatob, Elvis, Krichene, Syrine

“…Determinantal point processes (DPPs) have attracted substantial attention as an elegant probabilistic model that captures the balance between quality and…”
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Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes by Gartrell, Mike, Han, Insu, Dohmatob, Elvis, Gillenwater, Jennifer, Brunel, Victor-Emmanuel

“…Determinantal point processes (DPPs) have attracted significant attention in machine learning for their ability to model subsets drawn from a large item…”
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The Bayesian Low-Rank Determinantal Point Process Mixture Model by Gartrell, Mike, Paquet, Ulrich, Koenigstein, Noam

“…Determinantal point processes (DPPs) are an elegant model for encoding probabilities over subsets, such as shopping baskets, of a ground set, such as an item…”
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Low-Rank Factorization of Determinantal Point Processes for Recommendation by Gartrell, Mike, Paquet, Ulrich, Koenigstein, Noam

“…Determinantal point processes (DPPs) have garnered attention as an elegant probabilistic model of set diversity. They are useful for a number of subset…”
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GEVR: An Event Venue Recommendation System for Groups of Mobile Users by Zhang, Jason Shuo, Gartrell, Mike, Han, Richard, Lv, Qin, Mishra, Shivakant

“…In this paper, we present GEVR, the first Group Event Venue Recommendation system that incorporates mobility via individual location traces and context…”
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