Emil Carlsson

62 posts

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Emil Carlsson

Emil Carlsson

@ecarlsn

Reinforcement Learning and Statistics.

เข้าร่วม Ekim 2019
341 กำลังติดตาม74 ผู้ติดตาม
Emil Carlsson รีทวีตแล้ว
T3.com
T3.com@T3dotcom·
Sleep Cycle just gave its app an AI upgrade that could drastically improve your sleep t3.com/home-living/sl…
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Dr. Mwai Newton
Dr. Mwai Newton@Mwai_Newton·
Over the past five years, I’ve been focused on my PhD in machine learning, studying how to leverage historical data for interactive personalization, at Chalmers University in Sweden. For more on my work and other AI endeavours, visit newtonmwai.github.io!
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Emil Carlsson
Emil Carlsson@ecarlsn·
Work together with Herman Bergström, @frejohk and Devdatt Dubhashi
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Emil Carlsson
Emil Carlsson@ecarlsn·
Attending NeurIPS and interested in preference learning? Visit our poster today to learn about GURO, an active learning algorithm that greedily minimizes a bound on the ordering error to determine the next query. 📍 Session: West Ballroom, Booth 6604 🕚 Time: 11:00 AM - 2:00 PM
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Emil Carlsson
Emil Carlsson@ecarlsn·
I’m at NeurIPS this week presenting joint work with Herman Bergström, @frejohk and Devdatt Dubhashi on how to use context for better preference learning. Feel free to reach out if you want to discuss the paper! arxiv.org/pdf/2405.03059
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Fredrik Johansson
Fredrik Johansson@frejohk·
I'm at NeurIPS, eager to talk about the two papers from my group! The first, by Herman Bergström, Emil Carlsson, Devdatt Dubhashi, and me, explores how important context is to active preference learning for ordering items from pairwise comparisons: arxiv.org/abs/2405.03059
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Emil Carlsson
Emil Carlsson@ecarlsn·
I would also like to express my gratitude towards Kenny Smith, who served as the opponent during my public defense, as well as to the members of my grading committee: Karl Åström, @VerhoefTessa , and @ssshanest.
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Emil Carlsson
Emil Carlsson@ecarlsn·
I successfully defended my PhD thesis earlier this week! 😃👨‍🎓 It feels a bit weird not to be a student anymore😅 I am very grateful for all the support I've received from my supervisor, Devdatt Dubhashi, and my co-supervisor, @frejohk , throughout these years.
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Emil Carlsson
Emil Carlsson@ecarlsn·
🥲
Anthropic@AnthropicAI

Recommendation #1: Use the Central Limit Theorem Evaluation scores are usually mean scores across a large number of questions. This is a perfect fit for the Central Limit Theorem. In the paper, we suggest reporting the CLT-based standard errors alongside mean scores.

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Emil Carlsson
Emil Carlsson@ecarlsn·
A bit late to the party but our paper on active energy optimization with preference dynamics got accepted to the biggest Physics conference in Vancouver this year. Work together with Herman Bergström, @frejohk and Devdatt Dubhashi.
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Emil Carlsson รีทวีตแล้ว
IF Elfsborg
IF Elfsborg@IFElfsborg1904·
SEGER! #IFE | 1-0 | #ASR
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Fredrik Johansson
Fredrik Johansson@frejohk·
Searching for optimal decision-making policies without constraints typically results in universal recommendations: Always do A, not B! Not so if you have constraints on budget, diversity, side effects, etc. [1/2]
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Emtiyaz Khan
Emtiyaz Khan@EmtiyazKhan·
Call for papers for AISTATS 2025 is out now aistats.org/aistats2025/ca… You can also (self-)nominate for reviewer/AC position forms.gle/saediFoTznTQ7h… We are (trying to) switch to OpenReview so submission details will be available a bit later. @StephanMandt @liyzhen2 @ashipra 1/
Emtiyaz Khan@EmtiyazKhan

AISTATS 2025 will also be held in Asia (Phuket, Thailand) the following week (May 1 I think). I will co-chair with @ashipra. Easy to fly from Singapore (just 2 hours direct flight for around $100). The venue, right next to the beach. Plan to attend both ICLR and AISTATS in Asia!

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Debabrota Basu
Debabrota Basu@BasuDebabrota·
As bandits serve as the cornerstone of decision making with incomplete info & sequential interactions (e.g. recommenders), privacy becomes a pressing concern. We show #DifferentialPrivacy for (some) bandits is free. Is it true for contextual bandits also? #COLT2024 #openproblem
Scool@InriaScool

We've derived tight lower and upper bounds for differentially private finite-armed & linear bandits, while we lack the same for contextual bandits. At #COLT2024, @achraf_azize presents open problems in contextual bandits with privacy. @BasuDebabrota @Inria_Lille @RechercheUlille

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Emil Carlsson
Emil Carlsson@ecarlsn·
“Borderline reject”
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