Risk and Optimal Policies in Bandit Experiments (Adusumilli 2025) | FT50 ECTA episode artwork

EPISODE · Jul 16, 2025 · 31 MIN

Risk and Optimal Policies in Bandit Experiments (Adusumilli 2025) | FT50 ECTA

from Revise and Resubmit - The Mayukh Show · host Mayukh Mukhopadhyay

English Podcast Start at 00:00:00Bengali Podcast Start at 00:15:04Hindi Podcast Start at 00:24:06🎙️🎧 Welcome back to Revise and Resubmit! 🎧🎙️The podcast where the ink is never dry, the margins are full of notes, and the footnotes have footnotes!📈 Today’s episode isn’t just about statistics. It’s not just about algorithms.It’s about risk.It’s about strategy.It’s about the art and math of making the smartest decision… when you’re flying blind.👨‍🔬 Imagine you’re running a website, testing which headline gets more clicks.Or choosing the best drug in a clinical trial.You don’t know the future. But you still have to act.How do you make the best choice… with incomplete information?And how do you make sure your risk isn’t just minimized… but asymptotically optimal?🧠✨ In this mind-bending paper titled "Risk and Optimal Policies in Bandit Experiments", Karun Adusumilli brings decision theory to the frontlines of uncertainty. Published in the prestigious 🏛️ Econometrica—yes, an FT50 journal, folks—this work cracks open the world of bandit experiments, and uses partial differential equations (PDEs!) to chart the optimal course through chaos.🚀 From mathematical elegance to practical impact, this paper shows that with the right model, and the right math, we can slash the risk of traditional methods like Thompson Sampling—cut in half, no less! 😮Monte Carlo methods? Sparse matrix routines? That’s not just fancy math—it’s your new secret weapon.💡But here’s the kicker:If all bandit problems can be asymptotically reduced to Gaussian models with just two key state variables…👉 What else might we be overcomplicating in the world of decision-making?🫡 A massive thank you to Karun Adusumilli for this groundbreaking contribution, and to the publisher John Wiley & Sons Ltd, on behalf of the Econometric Society, for bringing it to the world.🌟 Remember—Econometrica is not just any journal. It's one of the best. One of the elite. It's on the FT50 list. So this isn’t just research—it’s research that matters.📲 Subscribe to our podcast Revise and Resubmit on Spotify, or check out the visuals on YouTube at Weekend Researcher.We’re also streaming now on Amazon Prime and Apple Podcast—so wherever your ears or eyes go, we’re there!🧪💥 This is Revise and Resubmit—where great ideas get a second draft……and sometimes, that draft rewrites the game.ReferenceAdusumilli, K. (2025), Risk and Optimal Policies in Bandit Experiments. Econometrica, 93: 1003-1029. https://doi.org/10.3982/ECTA21075‌‌Youtube Channel⁠https://www.youtube.com/@weekendresearcher⁠Support us on Patreonhttps://patreon.com/weekendresearcher

English Podcast Start at 00:00:00Bengali Podcast Start at 00:15:04Hindi Podcast Start at 00:24:06🎙️🎧 Welcome back to Revise and Resubmit! 🎧🎙️The podcast where the ink is never dry, the margins are full of notes, and the footnotes have footnotes!📈 Today’s episode isn’t just about statistics. It’s not just about algorithms.It’s about risk.It’s about strategy.It’s about the art and math of making the smartest decision… when you’re flying blind.👨‍🔬 Imagine you’re running a website, testing which headline gets more clicks.Or choosing the best drug in a clinical trial.You don’t know the future. But you still have to act.How do you make the best choice… with incomplete information?And how do you make sure your risk isn’t just minimized… but asymptotically optimal?🧠✨ In this mind-bending paper titled "Risk and Optimal Policies in Bandit Experiments", Karun Adusumilli brings decision theory to the frontlines of uncertainty. Published in the prestigious 🏛️ Econometrica—yes, an FT50 journal, folks—this work cracks open the world of bandit experiments, and uses partial differential equations (PDEs!) to chart the optimal course through chaos.🚀 From mathematical elegance to practical impact, this paper shows that with the right model, and the right math, we can slash the risk of traditional methods like Thompson Sampling—cut in half, no less! 😮Monte Carlo methods? Sparse matrix routines? That’s not just fancy math—it’s your new secret weapon.💡But here’s the kicker:If all bandit problems can be asymptotically reduced to Gaussian models with just two key state variables…👉 What else might we be overcomplicating in the world of decision-making?🫡 A massive thank you to Karun Adusumilli for this groundbreaking contribution, and to the publisher John Wiley & Sons Ltd, on behalf of the Econometric Society, for bringing it to the world.🌟 Remember—Econometrica is not just any journal. It's one of the best. One of the elite. It's on the FT50 list. So this isn’t just research—it’s research that matters.📲 Subscribe to our podcast Revise and Resubmit on Spotify, or check out the visuals on YouTube at Weekend Researcher.We’re also streaming now on Amazon Prime and Apple Podcast—so wherever your ears or eyes go, we’re there!🧪💥 This is Revise and Resubmit—where great ideas get a second draft……and sometimes, that draft rewrites the game.ReferenceAdusumilli, K. (2025), Risk and Optimal Policies in Bandit Experiments. Econometrica, 93: 1003-1029. https://doi.org/10.3982/ECTA21075‌‌Youtube Channel⁠https://www.youtube.com/@weekendresearcher⁠Support us on Patreonhttps://patreon.com/weekendresearcher

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Risk and Optimal Policies in Bandit Experiments (Adusumilli 2025) | FT50 ECTA

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English Podcast Start at 00:00:00Bengali Podcast Start at 00:15:04Hindi Podcast Start at 00:24:06🎙️🎧 Welcome back to Revise and Resubmit! 🎧🎙️The podcast where the ink is never dry, the margins are full of notes, and the footnotes have...

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