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06/05/2023
Weakly-Supervised Conditional Embedding for Referred Visual Search
This paper presents a new approach to image similarity search in the con...
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07/21/2022
Optimal precision for GANs
When learning disconnected distributions, Generative adversarial network...
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01/31/2022
Lessons from the AdKDD'21 Privacy-Preserving ML Challenge
Designing data sharing mechanisms providing performance and strong priva...
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11/30/2021
EdiBERT, a generative model for image editing
Advances in computer vision are pushing the limits of im-age manipulatio...
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10/19/2021
Latent reweighting, an almost free improvement for GANs
Standard formulations of GANs, where a continuous function deforms a con...
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07/03/2020
Do Not Mask What You Do Not Need to Mask: a Parser-Free Virtual Try-On
The 2D virtual try-on task has recently attracted a great interest from ...
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06/08/2020
Learning disconnected manifolds: a no GANs land
Typical architectures of Generative AdversarialNetworks make use of a un...
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06/04/2019
End-to-End Learning of Geometric Deformations of Feature Maps for Virtual Try-On
The 2D virtual try-on task has recently attracted a lot of interest from...
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02/23/2019
Distributionally Robust Reinforcement Learning
Generalization to unknown/uncertain environments of reinforcement learni...
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08/03/2018
Visual Reasoning with Multi-hop Feature Modulation
Recent breakthroughs in computer vision and natural language processing ...
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07/23/2018
Recurrent Neural Networks for Long and Short-Term Sequential Recommendation
Recommender systems objectives can be broadly characterized as modeling ...
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05/24/2018
Basket Completion with Multi-task Determinantal Point Processes
Determinantal point processes (DPPs) have received significant attention...
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07/02/2017
Modulating early visual processing by language
It is commonly assumed that language refers to high-level visual concept...
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03/15/2017
End-to-end optimization of goal-driven and visually grounded dialogue systems
End-to-end design of dialogue systems has recently become a popular rese...
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03/02/2016
Hybrid Collaborative Filtering with Autoencoders
Collaborative Filtering aims at exploiting the feedback of users to prov...
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07/10/2014
Bandits Warm-up Cold Recommender Systems
We address the cold start problem in recommendation systems assuming no ...
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05/14/2014
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques
In many recommendation applications such as news recommendation, the ite...
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10/22/2012