Memory leak in a Python project

owlet.today/posts/memory-leak-in-a-python-project/

2404.16130v1.pdf

arxiv.org/pdf/2404.16130

jp5ReklDNpcnUnZY_zaT8RbqN_ZprXqjydz4_lBE1Y6qU4ZnyjzC9h9q2ltpmGuzj798wxI2J6d_QpEuliDnVyvaBfILoc1_Y3nv-_Yf9oAw2dx9sg0i48KFPDVrv10LlqnEnC-YLrdE3WoApleV2v546UlRx5msXtKMzlV7LIU7CqwXcAesODe1UAQgY3zhw3vzlBIdUrVj13wMfvqz4A5rVDHd (285×214)

link-thumb.1vn.app/jp5ReklDNpcnUnZY_zaT8RbqN_ZprXqjydz4_lBE1Y6qU4ZnyjzC9h9q2ltpmGuzj798wxI2J6d_QpEuliDnVyvaBfILoc1_Y3nv-_Yf9oAw2dx9sg0i48KFPDVrv10LlqnEnC-YLrdE3WoApleV2v546UlRx5msXtKMzlV7LIU7CqwXcAesODe1UAQgY3zhw3vzlBIdUrVj13wMfvqz4A5rVDHd

1910.12840v1.pdf

arxiv.org/pdf/1910.12840

2404.12096v2.pdf

arxiv.org/pdf/2404.12096

2402.05672v1.pdf

arxiv.org/pdf/2402.05672

User preference modeling in a recommender system

substack.com/inbox/post/144215856

2309.08210v1.pdf

arxiv.org/pdf/2309.08210

2312.02724.pdf

arxiv.org/pdf/2312.02724.pdf

2311.11045.pdf

arxiv.org/pdf/2311.11045.pdf

EMNLP2019-NRMS.pdf

wuch15.github.io/paper/EMNLP2019-NRMS.pdf

Learning to Learn

hbr.org/2016/03/learning-to-learn

AI Watermarking 101: Tools and Techniques

huggingface.co/blog/watermarking

A Visual Guide to Mamba and State Space Models

maartengrootendorst.substack.com/p/a-visual-guide-to-mamba-and-state?utm_source=post-email-title&publication_id=1741130&post_id=141228095&utm_campaign=email-post-title&isFreemail=true&r=12vrjf&utm_medium=email

khoahocdulieu.github.io/2021/07/16/OT1.html

2402.08268.pdf

arxiv.org/pdf/2402.08268.pdf

gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling - 2308.07192.pdf

arxiv.org/pdf/2308.07192.pdf

2401.07519.pdf

arxiv.org/pdf/2401.07519.pdf

2312.00752.pdf

arxiv.org/pdf/2312.00752.pdf

State-Space Modelling

kevinkotze.github.io/ts-4-state-space/

2308.06721.pdf

arxiv.org/pdf/2308.06721.pdf

Push Notifications - What to Push, What Not to Push, and How Often

eugeneyan.com/writing/push/

Mixture of Experts Explained

huggingface.co/blog/moe

2311.12908.pdf

arxiv.org/pdf/2311.12908.pdf

Advantage Actor-Critic (A2C) - Hugging Face Deep RL Course

huggingface.co/learn/deep-rl-course/unit6/advantage-actor-critic

Practical Tips for Finetuning LLMs Using LoRA (Low-Rank Adaptation)

substack.com/inbox/post/138081202

Positive, Negative and Neutral: Modeling Implicit Feedback in Session-based News RecommendationPositive, Negative and Neutral: Modeling Implicit Feedback in Session-based News Recommendation - 2205.06058.pdf

arxiv.org/pdf/2205.06058.pdf

News Graph: An Enhanced Knowledge Graph for News Recommendation - kars2019.pdf

www.microsoft.com/en-us/research/uploads/prod/2019/09/kars2019.pdf

The hidden forces behind China's content king Toutiao : YC Startup Library | Y Combinator

www.ycombinator.com/library/3x-the-hidden-forces-behind-china-s-content-king-toutiao

2207.12598.pdf

arxiv.org/pdf/2207.12598.pdf

Speech synthesis: A review of the best text to speech architectures with Deep Learning | AI Summer

theaisummer.com/text-to-speech/

Real-time Retrieval for Recommendations

applyingml.com/resources/real-time-recommendations/

A forty-year career.

lethain.com/forty-year-career/

Generative Modeling by Estimating Gradients of the Data Distribution | Yang Song

yang-song.net/blog/2021/score/

Guidance: a cheat code for diffusion models

sander.ai/2022/05/26/guidance.html

1907.09682.pdf

arxiv.org/pdf/1907.09682.pdf

DreamBooth

huggingface.co/docs/diffusers/training/dreambooth

The Illustrated Stable Diffusion

jalammar.github.io/illustrated-stable-diffusion/

TF Recommenders: Encode user watch history using OpenAI embeddings | Xmartlabs Blog

blog.xmartlabs.com/blog/tf-recommenders-encode-user-watch-history-using-openai-embeddings/

1302_towards_good_practices_in_self.pdf

openreview.net/pdf?id=YYvtmM9TPw

Understanding self-supervised and contrastive learning with "Bootstrap Your Own Latent" (BYOL)

imbue.com/research/2020-08-24-understanding-self-supervised-contrastive-learning/

Weights & Biases

wandb.ai/wandb_fc/Normalization-Series/reports/Instance-Normalization-in-PyTorch-With-Examples---VmlldzoxNDIyNTQx

1809.10341.pdf

arxiv.org/pdf/1809.10341.pdf

Reinforcing User Retention in a Billion Scale Short Video Recommender SystemReinforcing User Retention in a Billion Scale Short Video Recommender System - 2302.01724.pdf

arxiv.org/pdf/2302.01724.pdf

How to Give a Killer Presentation

hbr.org/2013/06/how-to-give-a-killer-presentation

Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation - 2308.04086.pdf

arxiv.org/pdf/2308.04086.pdf

scontent.fsgn2-5.fna.fbcdn.net/v/t39.8562-6/246721374_422204999475172_9039387325224382577_n.pdf?_nc_cat=104&ccb=1-7&_nc_sid=ad8a9d&_nc_ohc=gZnE0wd2iBQAX9Lka7I&_nc_ht=scontent.fsgn2-5.fna&oh=00_AfCyutsR4g_o0uHkvzv7M3WWf6Jzo4c9NHD58DZK1jK_og&oe=64F3FD3A

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models - 2301.12597.pdf

arxiv.org/pdf/2301.12597.pdf

Scaling the Instagram Explore recommendations system

engineering.fb.com/2023/08/09/ml-applications/scaling-instagram-explore-recommendations-system/

PIE: Personalized Interest Exploration for Large-Scale Recommender SystemsPIE: Personalized Interest Exploration for Large-Scale Recommender Systems - 2304.06844.pdf

arxiv.org/pdf/2304.06844.pdf

(33) RecSys 2020 Tutorial: Feature Engineering for Recommender Systems - YouTube

www.youtube.com/watch?v=uROvhp7cj6Q