Very insightful article: Classical composers ignore amateur music making at their peril Edward Caine https://substack.com/home/post/p-195502594 Here are some quotes that I find contain profound and sharp diagnose of the industry. If you find it interesting, make sure to check out the OG article (link above). All rights belong to Mr Caine. As students, musicians often view amateur performance with a certain haughty scepticism and give it a wide berth, feeling that if they end up involved in amateur performance they are somehow “sliding backwards” from a position of a professional career. ...

The University of Chicago’s billenial concerto competition winner showcase took place today: here’s a recording of the performance: In particular, Anthony Yoon performs Tchaikovsky’s Violin Concerto In D Major, Op. 35 mvt I with the Symphony Orchestra, where he is also one of the 2nd violins. Both the orchestra and Anthony did a great job, I can guarantee you that we’re together (most of the times)

Professor Auster came to Chicago to give a talk in our theory seminar. Turns out for Pandora’s box, if boxes’ prior are ambiguous and decision maker seeks to minimize maximum regret against a clairvoyant oracle (an oracle who knows all the real reward of the boxes), the decision maker would exihbit choice overload (theoretically). Some additional notes on how to think about it using Yao’s (or Neumann’s) minmax lemma: Setup A decision maker face $n$ boxes. Search cost $c_i$ for each boxes. Each box’s reward is binary $v_i \in \{0, \bar v\}$. ...

Mechanism design is a framework for studying the set of implementable outcomes when rational agents have private information. Revelation principle is one of its key lemmas. Here’s a principled way to understand it: Setup Agents: $i \in [n] = \{1, \dots, n\}$. Types: Each agent $i$ has private type $t_i \in T_i$. The joint type space is $T = \prod_{i=1}^n T_i$. Prior: The type distribution (common prior) is $q \in \Delta(T)$. Assume $q$ is fully supported on $T$, i.e., $q(t) > 0$ for all $t \in T$. Outcomes: $x \in X$. Preferences: Each agent $i$ has a VNM utility function contingent on the outcome and the types of all agents: $$u_i : X \times T \to \mathbb{R}.$$ General Mechanism Definition. A (general) mechanism is a pair $(S, g)$, where $S = S_1 \times \cdots \times S_n$, with $S_i$ the set of strategies (messages) available to agent $i$, and $g$ is a (possibly stochastic) outcome function: ...

The VAR Model We observe a vector time series $Z_1, Z_2, \ldots, Z_T \in \mathbb{R}^m$ following a VAR($\ell$): $$ Z_{t+1} = \tilde {\mathbb N} + D \begin{pmatrix} Z_t \\ Z_{t-1} \\ \vdots \\ Z_{t-\ell+1} \end{pmatrix} + F\,W_{t+1}, \qquad W_{t+1} \sim \mathcal{N}(0, I_k). \tag{1} $$Known: the signals $Z_1, \ldots, Z_T$. Unknown: the coefficient matrices $\tilde {\mathbb N}$, $D$, and the covariance $FF'$. Key idea. Treat $(\tilde {\mathbb N}, D)$ as hidden states that never change, so the problem becomes an Hidden Markdov Model (HMM) with trivial state dynamics $\beta_{t+1} = \beta_t$ and a linear observation equation. We then update beliefs about $\beta$ recursively as data arrives. ...

以史为鉴, 可以知兴替 Using history as a mirror, one can predict a dynasty’s future. Some operations research archeology: Kantorovich and Zalgaller (1951): the 0-th column generation algorithm Eduardo Uchoa, Ruslan Sadykov. Mathematical Programming, 2026. This article probes the origins of the Column Generation technique. It begins with Kantorovich’s classic 1939 work, correcting widespread misconceptions about his contributions to the Cutting Stock Problem. It then brings to light Kantorovich and Zalgaller’s lesser-known 1951 book, which is revealed to contain a complete Column Generation algorithm. The article also places these contributions in the context of the turbulent USSR’s political and ideological environment, essential for a deeper understanding of their significance. ...

Professor Shleifer come over to Booth to talk in our Monday macro/intermational economic workshop. He’s so popular that we have to move to the largest classroom and it is filled. The admin bought enough sandwich for everyone though The Psychology of Macroeconomic Expectations Bordalo, Gennaioli, Lopez de Silanes, Schroeder, Shleifer, van Rooij (2026) There’s a version online in Booth’s website: https://www.chicagobooth.edu/-/media/project/chicago-booth/faculty-and-insights/research-workshops/shleifer.pdf Behavioral economics and general economic theory have left an open question in modeling: whether non-domain-specific (NDS) experiences — a health crisis, a divorce, financial hardship — could causally shift macro beliefs through a psychological, non-informational channel. This paper did the job: ...

Contemporary program: Joyce Light and Dark Villa-Lobos Assobio a Jato (“Jet Whistle”) for flute and cello Shaw Boris Kerner for cello + flower pots Chen Yi Qi for flute, cello, percussion, piano Dehnhard WAKE UP! for piccolo and alarm clock Gosfield Daughters of the Industrial Revolution Farrenc Piano Trio No. 4 in E Minor, Op. 45 What a program. When UChicago hands the reins to the artists themselves (according to Cynthia Yeh in the post-concert panel) — letting artists choose what they actually want to play — the results speak for themselves. No institutional hedging, no safe overtures. What we got instead was a concert of proper, fearless, genuinely good contemporary music. And the ensemble really CSO’s chamber music dream team: ...

You can shuffle allocation, but competition is still there: 重磅：广州将不分重点班！小学和初中新生或“一键分班” Source: 羊城晚报 (Yangcheng Evening News), by 蒋隽, April 15, 2026. Link Breaking News: Starting September 2026, Guangzhou will ban tracked classes (重点班) in all Grade 1 and Grade 7 cohorts. Students and teachers will be randomly assigned via a centralized “one-click” system. The core mechanism is DOUBLE RANDOMIZATION! “9月新学年入学的一年级和初一新生将在教育部门组织及监管下’一键分班’，同时老师也将随机匹配” “Grade 1 and Grade 7 students entering in September will be ‘one-click assigned’ under the organization and supervision of the education bureau; teachers will also be randomly matched.” ...

Erdodic’s Wikipedia definition is very general (and confusing) — “time averages equal ensemble averages”? Here’s a simplified version for finite-state markov chain: Let $\{X_k\}_{k \geq 0}$ be a Markov chain on state $S$. Let $\pi\in \Delta(S)$. Let Let transition operatro be $P$, so $\pi^{t + 1} = P \pi^t$. Define stationary distribution $\bar \pi$ as $X_0 \sim \bar \pi$ where $P\bar\pi = \bar\pi$, the stationary process satisfies $$ (X_0, X_1, \dots) \overset{d}{=} (X_1, X_2, \dots) $$ Definition. The stationary process $\{X_k\}$ is ergodic if for every bounded function $f: S \to \mathbb{R}$ the following convergence hold a.s.: ...