Financial news can influence investment decisions long after publication. Timely news may reach an investor before prices fully adjust, whereas older news may already be reflected in prices. We examine two ways to handle aging signals: retain them and give a portfolio policy timing information, or filter them out befor...
Bolin Song (Cornell University), Surui Xiang (United Nations)· 0 citations
Real-world data often exhibits cluster structure at multiple resolutions, yet existing methods typically learn a single partition or construct an explicit hierarchy. Inspired by Matryoshka Representation Learning, we introduce NEST, an unsupervised framework that encodes coarse-to-fine structure within a single embeddi...
Which pretraining objective yields the best representation for downstream tasks under an information budget? We formalize this problem as a multitask information bottleneck, using a mutual information constraint to model incomplete information retention. For Gaussian inputs and tasks, we characterize optimal representa...
Sparse autoencoders (SAEs) were originally motivated by discovering monosemantic features, a property that characterizes individual features but does not specify what the learned feature set should look like as a whole. As SAEs have increasingly been adopted for attribution, circuit discovery, and intervention, researc...
Riteng Zhang, Xiaoqian Wang· 0 citations
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Conditional generation is a key capability to be supported by Large Tabular Models, enabling a number of applications. Accurate conditional generation has to contend with two key challenges: $(i)$ Data comprise a mixture of numerical and categorical entries, the latter often with high cardinality and heavily unbalanced...
Alankrita Bhatt, Mukur Gupta, Andrea Montanari et al.· 0 citations
This work introduces Short-to-Long (S2L), which supplies a long-horizon behavior learner with features trained by smaller-discount source networks, which yields aggregate performance gains, improving the paired terminal median on 40 of 57 Atari games.
Cheng-Quan Tong, B. Ivanovic, Marco Pavone· 0 citations
aggmetrics is a Python package that extends any binary performance measure expressed in the four confusion-matrix counts to multiclass, multilabel, ordinal, cost-sensitive, soft-label and cross-validation settings, by substituting one of four aggregation operators for what libraries usually expose as an average switch....
This paper proposes a theory-guided perturbation strategy that selects structurally influential signed-edge modifications and shows that the proposed method consistently induces larger embedding drift, polarity change, and downstream link prediction degradation than baselines.
This work proposes a swap-based local search that decreases the bound at every accepted step and can refine the output of any selector without worsening its bound, and provides experimental results on CIFAR10 and CIFAR100 showing that it matches existing data selection baselines.
Ahmed Mehdi Inane, Mahdi Haghifam, G. Dziugaite et al.· 0 citations
Recent work in additive manufacturing and neural inverse design enables the creation of complex three-dimensional structures to manipulate physical fields, yet these designs must also adhere to discrete, non-differentiable fabrication constraints. Current methods limit the design space by imposing differentiable soft m...
Shanmuka Sadhu, Harshvardhan C. Takawale, Yehia Zakaria et al.· 0 citations
It is demonstrated that random-split evaluation obscures meaningful differences in representation quality and identifies topological representations as an effective inductive bias for learning under structured biological distribution shift.
Arezoo Bybordi, Favour Achimba, Mariam Gelashvili et al.· 0 citations
The Bayesian fixed-confidence best-arm identification problem in which a learner can abstain from making a terminal recommendation is studied and Screen-and-Confirm (S&C) is proposed and its expected stopping time is analyzed.
Yu-Qi Huang, Yun-Long Hou, Vincent Y. F. Tan· 0 citations
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.
MIT News · Artificial Intelligence· news.mit.eduOct 28, 2026
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
MIT News · Artificial Intelligence· news.mit.eduOct 27, 2026
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
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