RASCAL is an untethered robot with a modular design, allowing it to move flexibly along and between evenly spaced storage shelves. Discover how it can address the availability and scalability challenges of existing automated storage and retrieval systems.
REGISTER NOW: https://aka.ms/ResearchForum_YTReg (opens in new tab)AI is transforming the way we all live, work, and think. Join us for Microsoft Research Forum, where you'll learn about the most recent advances and hear bold new ideas from the global research community. See you on September…
Speaker(s): Eloi MolinerHost: Hannes Gamper Speech reverberation control involves the manipulation of acoustic characteristics in speech recordings, including tasks like speech dereverberation or reverberation time reduction. Diffusion implicit bridges are a recently proposed domain translation technique based on diffusion models and entropy-regularized optimal transport. They…
Explaining deep learning models operating on time series data is crucial in various applications of interest which require interpretable and transparent insights from time series signals. In this work, we investigate this problem from an information theoretic perspective and show that most existing measures of…
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In recent years, autoscaling has garnered significant attention in cloud computing, emphasizing cost efficiency, performance optimization, and availability for dynamic workloads. New algorithms for horizontal, vertical, and hybrid scaling, targeting instances, VM specifications, and resources like CPU, memory, and IO, have emerged. Various approaches, including…
Autoscaling can optimize cloud resource usage and costs by adjusting to demand. VASIM shows that simplifying testing and refinement of autoscaling algorithms can enable rapid development and evaluation of more efficient & cost-effective autoscaling strategies.
Property prediction for materials under realistic conditions has been a long-standing challenge within the digital transformation of materials design. MatterSim investigates atomic interactions from the very fundamental principles of quantum mechanics.
On may 13th Openai unveiled its latest model, gpt-4o. Mira Murati, the company’s chief technology officer, called it the “future of interaction between ourselves and the machines”, because users will be able to speak to the model, which will talk back in an expressive, humanlike…
The high false positive (FP) rate of authentication alerts remains to be a prominent challenge in cybersecurity nowadays. We identify two problems that cause this issue, which are unaddressed in existing learning-based anomaly detection methods. First, in industrial applications, ground-truth labels for malicious authentication events…
Recent advances in knowledge graph embedding (KGE) rely on Euclidean/hyperbolic orthogonal relation transformations to model intrinsic logical patterns and topological structures. However, existing approaches are confined to rigid relational orthogonalization with restricted dimension and homogeneous geometry, leading to deficient modeling capability. In this work, we…
Recent breakthroughs in large models have highlighted the critical significance of data scale, labels and modals. In this paper, we introduce MS MARCO Web Search, the first large-scale information-rich web dataset, featuring millions of real clicked query-document labels. This dataset closely mimics real-world web document…
