10 citations · 23 across the 8 of their papers we have counts for
3 papers · 1 filter
On Symmetric Pseudo-Boolean Functions: Factorization, Kernels and Applications
Richik Sengupta, Jacob Biamonte
A symmetric pseudo-Boolean function is a map from Boolean tuples to real numbers which is invariant under input variable interchange. We prove that any such function can be equival…
Tensor networks in machine learning
Richik Sengupta, Soumik Adhikary, Ivan Oseledets +1
A tensor network is a type of decomposition used to express and approximate large arrays of data. A given data-set, quantum state or higher dimensional multi-linear map is factored…
Ion native variational ansatz for quantum approximate optimization
Daniil Rabinovich, Soumik Adhikary, Ernesto Campos +6
Variational quantum algorithms involve training parameterized quantum circuits using a classical co-processor. An important variational algorithm, designed for combinatorial optimi…