Map Interface for Control of Smart Home Appliances

As homeowners increasingly adopt and install smart appliances and devices, differentiating such appliances and devices by names has become difficult. For example, a typical house may have tens of appliances such as lights, computers, televisions, audio units, game consoles, heaters, air-conditioners, etc. Attempting to control such appliances/devices by assigning names can become tedious and error-prone. This disclosure describes techniques that visually situate home appliances on an indoor map. To control an appliance, a user can quickly select an appliance by its location on the map

Energy Savings Using Virtual Assistants and Smart Home Appliances

This disclosure describes techniques to monitor and control smart home devices through virtual assistants. Use of the techniques can result in substantial energy savings

Automatic content filtering in virtual assistants for kids

Virtual assistant responses need to be both useful and safe for kids and families. However, this is currently not always the case. For example, virtual assistant responses can sometimes unexpectedly include explicit answers or answers that are otherwise unsuitable for kids. However, restricting searches can prevent the virtual assistant from surfacing useful, family-safe responses. There is no systematic way to filter non-textual media content, e.g., music, video, etc. Per the techniques of this disclosure, a library of content classifiers is provided that filters out various categories of content inappropriate for children, e.g., explicit content, violent content, etc. A query to a virtual assistant and the responses to the query are filtered by the classifiers. Depending on the context, e.g., current audience, the virtual assistant surfaces filtered responses to queries

Digital Sticky Notes

Sticky notes are commonly utilized for messages and/or reminders for the author of the note and/or other users. This disclosure describes digital sticky notes that can be shared using a computing device (such as a smart speaker) with other users that have physical access to the device. The digital sticky note enables content sharing and collaboration, without requiring a sign-in to the computing device by other users. A user can create a digital sticky note using a virtual assistant. With user permission, the digital sticky note is made visible on an ambient screen of the smart display to all users and is automatically synchronized with other devices associated with the user account

Mouse behavior recognition with the wisdom of crowd

Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 67-72).In this thesis, we designed and implemented a crowdsourcing system to annotate mouse behaviors in videos; this involves the development of a novel clip-based video labeling tools, that is more efficient than traditional labeling tools in crowdsourcing platform, as well as the design of probabilistic inference algorithms that predict the true labels and the workers' expertise from multiple workers' responses. Our algorithms are shown to perform better than majority vote heuristic. We also carried out extensive experiments to determine the effectiveness of our labeling tool, inference algorithms and the overall system.by Yuzhao Ni.S.M

Robust Low-Rank Subspace Segmentation with Semidefinite Guarantees

Recently there is a line of research work proposing to employ Spectral Clustering (SC) to segment (group){Throughout the paper, we use segmentation, clustering, and grouping, and their verb forms, interchangeably.} high-dimensional structural data such as those (approximately) lying on subspaces {We follow {liu2010robust} and use the term "subspace" to denote both linear subspaces and affine subspaces. There is a trivial conversion between linear subspaces and affine subspaces as mentioned therein.} or low-dimensional manifolds. By learning the affinity matrix in the form of sparse reconstruction, techniques proposed in this vein often considerably boost the performance in subspace settings where traditional SC can fail. Despite the success, there are fundamental problems that have been left unsolved: the spectrum property of the learned affinity matrix cannot be gauged in advance, and there is often one ugly symmetrization step that post-processes the affinity for SC input. Hence we advocate to enforce the symmetric positive semidefinite constraint explicitly during learning (Low-Rank Representation with Positive SemiDefinite constraint, or LRR-PSD), and show that factually it can be solved in an exquisite scheme efficiently instead of general-purpose SDP solvers that usually scale up poorly. We provide rigorous mathematical derivations to show that, in its canonical form, LRR-PSD is equivalent to the recently proposed Low-Rank Representation (LRR) scheme {liu2010robust}, and hence offer theoretic and practical insights to both LRR-PSD and LRR, inviting future research. As per the computational cost, our proposal is at most comparable to that of LRR, if not less. We validate our theoretic analysis and optimization scheme by experiments on both synthetic and real data sets.Comment: 10 pages, 4 figures. Accepted by ICDM Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM), 2010. Main proof simplified and typos corrected. Experimental data slightly adde

Mouse Behavior Recognition with The Wisdom of Crowd

In this thesis, we designed and implemented a crowdsourcing system to annotatemouse behaviors in videos; this involves the development of a novel clip-based video labeling tools, that is more efficient than traditional labeling tools in crowdsourcing platform, as well as the design of probabilistic inference algorithms that predict the true labels and the workers' expertise from multiple workers' responses. Our algorithms are shown to perform better than majority vote heuristic. We also carried out extensive experiments to determine the effectiveness of our labeling tool, inference algorithms and the overall system

Preliminary comparison of tumor biologic factors in breast carcinomas from Australian and Chinese women

OBJECTIVE: To compare the morphologic and immunohistochemical properties of breast carcinomas from Chinese and Australian women in order to define possible biologic differences between these carcinomas