2 citations · 3 across the 7 of their papers we have counts for
10 papers
Sensitivity of Filter Kernels and Robustness Bounds to Transition and Measurement Kernel Perturbations in Partially Observable Stochastic Control
Yunus Emre Demirci, Ali Devran Kara, Serdar Yüksel
Studying the stability of partially observed Markov decision processes (POMDPs) with respect to perturbations in either transition or observation kernels is a significant problem.…
Refined Bounds on Near Optimality Finite Window Policies in POMDPs and Their Reinforcement Learning
Yunus Emre Demirci, Ali Devran Kara, Serdar Yüksel
Finding optimal policies for Partially Observable Markov Decision Processes (POMDPs) is challenging due to their uncountable state spaces when transformed into fully observable Mar…
Average Cost Optimality of Partially Observed MDPS: Contraction of Non-linear Filters, Optimal Solutions and Approximations
Yunus Emre Demirci, Ali Devran Kara, Serdar Yüksel
The average cost optimality is known to be a challenging problem for partially observable stochastic control, with few results available beyond the finite state, action, and measur…
Unique Ergodicity of Non-Linear Filters via Reachability and Uniform Weak Continuity
Yunus Emre Demirci, Serdar Yüksel
We present a reachability based approach to establish unique ergodicity of non-linear filter processes where state space of a hidden Markov model is a compact Polish metric space a…
Mixing time bounds for edge flipping on regular graphs
Yunus Emre Demirci, Ümit Işlak, Alperen Özdemir
The edge flipping is a non-reversible Markov chain on a given connected graph, which is defined by Chung and Graham. In the same paper, its eigenvalues and stationary distributions…
Mixing time bounds for edge flipping on regular graphs
Yunus Emre Demirci, Ümit Işlak, Alperen Yaşar Özdemir
The edge flipping is a non-reversible Markov chain on a given connected graph, which is defined by Chung and Graham in [CG12]. In the same paper, its eigenvalues and stationary dis…