Kuno Kim (@_kunoai) 's Twitter Profile
Kuno Kim

@_kunoai

PhD Student @StanfordAILab #AI #ML

ID: 1182327242736586752

calendar_today10-10-2019 16:09:59

12 Tweet

53 Followers

31 Following

Rui Shu (@_smileyball) 's Twitter Profile Photo

New paper on disentanglement c: Given the recent impossibility results in unsupervised disentanglement, we decided to be optimistic and instead provide guarantees (unimpossibility results?) via weak supervision (1/13) arxiv.org/abs/1910.09772 git.io/Je0gN

Horace He (@chhillee) 's Twitter Profile Photo

Some metadata for those curious about their #ICLR2020 reviews. 1. Histogram of the average reviews. 2. Top x% deciles Seems like reviews this year at ICLR 2026 are substantially lower than previous years. Probably an artifact of the new [1,3,6,8] reviewing system. (1/n)

Some metadata for those curious about their #ICLR2020 reviews.

1. Histogram of the average reviews.
2. Top x% deciles

Seems like reviews this year at <a href="/iclr_conf/">ICLR 2026</a> are substantially lower than previous years. Probably an artifact of the new [1,3,6,8] reviewing system. (1/n)
Daniel Yamins (@dyamins) 's Twitter Profile Photo

3/3 Tomorrow 9am/11pmPT: Kuno Kim Active Learning with Progress Curiosity. New curiosity signal that is robust, scalable & strong. And leads to emergence of social attention behaviors! paper: arxiv.org/abs/2007.07853 Nick Haber Meg Sano Julian De Freitas

Kuno Kim (@_kunoai) 's Twitter Profile Photo

A new scalable and amazingly easy to implement Progress curiosity algorithm released! We report state-of-the-art sample efficiency results in agent-rich 3D environments. We hope to see researchers try it out in various other domains, e.g Atari, Mujoco!

Jason Lee (@jasondeanlee) 's Twitter Profile Photo

Predicting What You Already Know Helps: Provable Self-Supervised Learning We analyze how predicting parts of the input from other parts (missing patch, missing word, etc.) helps to learn a representation that linearly separates the downstream task. arxiv.org/abs/2008.01064 1/2

Predicting What You Already Know Helps: Provable Self-Supervised Learning
We analyze how predicting parts of the input from other parts (missing patch, missing word, etc.) helps to learn a representation that linearly separates the downstream task.
arxiv.org/abs/2008.01064 1/2
Animesh Garg (@animesh_garg) 's Twitter Profile Photo

This needs to be said out loud, particularly by gatekeepers of AI/ML academia (Profs, advisors, mentors, reviewers, SACs, ACs) Novelty for the sake of it is not a virtue! Many students trying to be different for the sake of novelty and often sacrificing utility in the process!

Daniel Yamins (@dyamins) 's Twitter Profile Photo

1/ Def'n: a "learning rule" is a functional that converts error signals (for some given objective function) to changes in system parameters (e.g. synaptic strengths) such that error decreases after iterated application.

Marc G. Bellemare (@marcgbellemare) 's Twitter Profile Photo

Our most recent work is out in Nature! We're reporting on (reinforcement) learning to navigate Loon stratospheric balloons and minimizing the sim2real gap. Results from a 39-day Pacific Ocean experiment show RL keeps its strong lead in real conditions. nature.com/articles/s4158…

Jiaming Song (@baaadas) 's Twitter Profile Photo

Can we make better use of negative samples in contrastive learning? In our #NeurIPS2020 paper, we show this is true by simply using a multi-label objective. Come to our oral presentation at 6:15 PT (neurips.cc/virtual/2020/p…) and poster at 9-11 for more details! Stefano Ermon

Can we make better use of negative samples in contrastive learning? In our #NeurIPS2020 paper, we show this is true by simply using a multi-label objective. Come to our oral presentation at 6:15 PT (neurips.cc/virtual/2020/p…) and poster at 9-11 for more details! <a href="/StefanoErmon/">Stefano Ermon</a>
Shengjia Zhao (@shengjia_zhao) 's Twitter Profile Photo

🚨 If a provider predicts that a vaccine is 95% effective for you, should you trust the 95% when making decisions? We show how to enable decisions with complete confidence. AISTATS oral happening in 1 hour virtual.aistats.org/virtual/2021/s… Blog ermongroup.github.io/blog/mechanism/

🚨 If a provider predicts that a vaccine is 95% effective for you, should you trust the 95% when making decisions? We show how to enable decisions with complete confidence.  

AISTATS oral happening in 1 hour 
virtual.aistats.org/virtual/2021/s… 
Blog ermongroup.github.io/blog/mechanism/