human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "resolution and the binary encoding of combinatorial principles"
  Abstract: We investigate the size complexity of proofs in $Res(s)$ -- an extension of Resolution working on $s$-DNFs instead of clauses -- for families of contradictions given in the {\em unusual binary} encoding. A motivation of our work is size lower bounds of refutations in Resolution for families of contradictions in the usual unary encoding. Our main interest is the $k$-Clique Principle, whose Resolution complexity is still unknown. #R##N#Our main result is a $n^{\Omega(k)}$ lower bound for the size of refutations of the binary $k$-Clique Principle in $Res(\lfloor \frac{1}{2}\log \log n\rfloor)$. This improves the result of Lauria, Pudl\'ak et al. [24] who proved the lower bound for Resolution, that is $Res(1)$. #R##N#Our second lower bound proves that in $RES(s)$ for $s\leq \log^{\frac{1}{2-\epsilon}}(n)$, the shortest proofs of the $BinPHP^m_n$, requires size $2^{n^{1-\delta}}$, for any $\delta>0$. Furthermore we prove that $BinPHP^m_n$ can be refuted in size $2^{\Theta(n)}$ in treelike $Res(1)$, contrasting with the unary case, where $PHP^m_n$ requires treelike $RES(1)$ \ refutations of size $2^{\Omega(n \log n)}$ [9,16]. #R##N#Furthermore we study under what conditions the complexity of refutations in Resolution will not increase significantly (more than a polynomial factor) when shifting between the unary encoding and the binary encoding. We show that this is true, from unary to binary, for propositional encodings of principles expressible as a $\Pi_2$-formula and involving {\em total variable comparisons}. We then show that this is true, from binary to unary, when one considers the \emph{functional unary encoding}. Finally we prove that the binary encoding of the general Ordering principle $OP$ -- with no total ordering constraints -- is polynomially provable in Resolution.

Connected through hyperedge HE-1 (induced by source paper "sherali adams and the binary encoding of combinatorial principles"):
  with members:
    - "sum of squares bounds for the total ordering principle"
    - "tight size degree bounds for sums of squares proofs"
    - "the complexity of proving that a graph is ramsey"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CC(Computational Complexity)