Abstract With the ongoing shift from off-line to on-line business processes, the Web has become an important business platform, and for most companies it is crucial to have an on-...
We propose a new framework for discussing computational complexity of problems involving uncountably many objects, such as real numbers, sets and functions, that can be represente...
ent abstract presents OASIS, an Online Algorithm for Scalable Image Similarity learning that learns a bilinear similarity measure over sparse representations. OASIS is an online du...
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
We propose rewriting logic as a unifying framework for a wide range of Petri nets models. We treat in detail place/transition nets and important extensions of the basic model by in...
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...