We consider the problem of classification using similarity/distance functions over data. Specifically, we propose a framework for defining the goodness of a (dis)similarity function with respect to a given learning task and propose algorithms that have guaranteed generalization properties when working with such good functions. Our framework unifies and generalizes the frameworks proposed by [1]...

Robot planning is the process of selecting a sequence of actions that optimize for a task specific objective. For instance, the objective for a navigation task would be to find collision free paths, while the objective for an exploration task would be to map unknown areas. The optimal solutions to such tasks are heavily influenced by the implicit structure in the environment, i.e. the configura...

In the LEC system, we employ a learning-driven approach for solving combinational data-path equivalence checking problems. The data-path logic is specified using Boolean and word-level operators in VHDL/Verilog. The targeted application area are Cto-RTL equivalence checking problems found in an industrial setting. These are difficult because of the algebraic transformations done on the data-pat...

Fuzzy modeling has many advantages over the non-fuzzy methods, such as robustness against uncertainties and less sensitivity to the varying dynamics of nonlinear systems. Data-driven fuzzy modeling needs to extract fuzzy rules from the input/output data, and train the fuzzy parameters. This paper takes advantages from deep learning, probability theory, fuzzy modeling, and extreme learning machi...

The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known Q-matrix, which specifies the item-attribute relationships. This article proposes a data-driven approach to identification of the Q-matrix and estimation of related model parameters. A key ingredient is a flexible ...

In distributed machine learning, data is dispatched to multiple machines for processing. Motivated by the fact that similar data points often belong to the same or similar classes, and more generally, classification rules of high accuracy tend to be “locally simple but globally complex” [45], we propose data dependent dispatching that takes advantage of such structure. We present an in-depth an...

Dedifferentiated liposarcoma (DDL) is a histologically pleomorphic sarcoma, traditionally defined as well-differentiated liposarcoma with abrupt transition to high grade, non-lipogenic sarcoma. It can occur as part of recurrent well-differentiated liposarcoma, or may arise de novo. DDL most frequently occurs within the retroperitoneum, and while it is prone to local recurrence, it usually has a...