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With deeptech becoming critical to business success, IISc's PG Level Advanced Certification programme in AI and MLOps is the right step towards building expertise in this domain

Spotlight News: With deeptech becoming critical to business success, IISc's PG Level Advanced Certification programme in AI and MLOps is the right step towards buildi ....

Tamil Nadu , United States , Ankit Agarwal , Sashikumaar Ganesan , Pg Level Advanced Certification Programme , Department Of Computational , Deepak Subramani Programme Coordinator , Ai Mlops Indian Institute Of Science , Data Sciences Iisc , Indian Institute Of Science , Data Sciences , Massachusetts Institute Of Technology , Iisc Centre For Continuing Education , Indian Institute Of Science Iisc , Research Trends , Research University , Artificial Intelligence , Advanced Certification Programme , Machine Learning , Indian Institute , Continuing Education , Programming Prerequisites , Computer Vision , Designing Machine Learning Systems , Natural Language Processing , Representation Learning ,

Matryoshka Representation Learning with CLIP for Multimodal Retrieval and Ranking

TL;DR We introduce Matryoshka Representation Learning (MRL), facilitating flexible embedding sizes in vector databases. This allows a balance between efficiency and granularity. Through MRL, embeddings condense into smaller dimensions while preserving performance in retrieval and ranking tasks. In summary, MRL empowers cost-effective flexibility without compromising performance in multimodal retrieval and ranking tasks. ....

Representation Learning , Generalized Contrastive Learning , Embedding Sizes , Minimal Impact , Original Embedding ,

"Boost Off/On-Manifold Adversarial Robustness for Deep Learning with La" by Mengdie Huang, Yi Xie et al.

Deep neural networks excel at solving intuitive tasks that are hard to describe formally, such as classification, but are easily deceived by maliciously crafted samples, leading to misclassification. Recently, it has been observed that the attack-specific robustness of models obtained through adversarial training does not generalize well to novel or unseen attacks. While data augmentation through mixup in the input space has been shown to improve the generalization and robustness of models, there has been limited research progress on mixup in the latent space. Furthermore, almost no research on mixup has considered the robustness of models against emerging on-manifold adversarial attacks. In this paper, we first design a latent-space data augmentation strategy called dual-mode manifold interpolation, which allows for interpolating disentangled representations of source samples in two modes: convex mixing and binary mask mixing, to synthesize semantic samples. We then propose a resilien ....

Latentrepresentationmixup Larepmixup , Adversarial Attack , Adversarial Robustness , Deep Neural Networks , Representation Learning ,

Computer vision system marries image recognition and generation

A new framework known as MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single cohesive system. The work was developed by researchers from MIT and Google. ....

Tianhong Li , Huiwen Chang , Dina Katabi , Shlok Kumar Mishra , Zhan Zhang , Dilip Krishnan , Huisheng Wang , Department Of Electrical Engineering , University Of Maryland Ph , Artificial Intelligence Laboratory , Google Research , Watson Research Collaboration , Masked Generative Encoder , Machine Intelligence , Nicole Pham Professor , Electrical Engineering , Computer Science , Maryland Phd , Google Cloud Platform , Computer Vision , Mit Csail , It Ibm Watson Research Collaboration , It Ai Research , Asked Generative Encoder Mage , Computer Vision , Image Generation ,

All languages are NOT created (tokenized) equal

Language models cost much more in some languages than others ....

New York , United States , Mark Dredze , Zhang Deyim Dianxin , Jin Tsu , Denys Linkov , Sebastian Ruder , Ivan Vuli , Matthews Haspelmath , Shijie Wu , Findings Of The Association For Computational Linguistics , Dimensional Exploration Of The Research Manifold , Danish National Archives , Association For Computational Linguistics , Techs World Wide Web Technology , Pair Encoding , Natural Language , World Wide Web Technology Surveys , Common Crawl , Representing Chinese Typography , Zhang Deyim , Google Fonts , Chinese Morse , Byte Pair Encoding , Huggingface Transformers , Token Distribution ,