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Pinyan Lu

Publications and source records attributed to Pinyan Lu.

At least 73 records · Page 4Linked to original sources

The Value of Information Concealment

We consider a revenue optimizing seller selling a single item to a buyer, on whose private value the seller has a noisy signal. We show that, when the signal is kept private, arbitrarily more revenue could potentially be extracted than if the signal is leaked or revealed. We then show that, if the seller is not allowed to make payments to the buyer, the gap between the two is bounded by a multiplicative factor of 3, if the value distribution conditioning on each signal is regular. We give examples showing that both conditions are necessary for a constant bound to hold. We connect this scenario to multi-bidder single-item auctions where bidders' values are correlated. Similarly to the setting above, we show that the revenue of a Bayesian incentive compatible, ex post individually rational auction can be arbitrarily larger than that of a dominant strategy incentive compatible auction, whereas the two are no more than a factor of 5 apart if the auctioneer never pays the bidders and if each bidder's value conditioning on the others' is drawn according to a regular distribution. The upper bounds in both settings degrade gracefully when the distribution is a mixture of a small number of regular distributions.

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Dichotomy for Real Holant$^c$ Problems

Holant problems capture a class of Sum-of-Product computations such as counting matchings. It is inspired by holographic algorithms and is equivalent to tensor networks, with counting CSP being a special case. A classification for Holant problems is more difficult to prove, not only because it implies a classification for counting CSP, but also due to the deeper reason that there exist more intricate polynomial time tractable problems in the broader framework. We discover a new family of constraint functions $\mathscr{L}$ which define polynomial time computable counting problems. These do not appear in counting CSP, and no newly discovered tractable constraints can be symmetric. It has a delicate support structure related to error-correcting codes. Local holographic transformations is fundamental in its tractability. We prove a complexity dichotomy theorem for all Holant problems defined by any real valued constraint function set on Boolean variables and contains two 0-1 pinning functions. Previously, dichotomy for the same framework was only known for symmetric constraint functions. he set $\mathscr{L}$ supplies the last piece of tractability. We also prove a dichotomy for a variant of counting CSP as a technical component toward this Holant dichotomy.

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An FPTAS for Counting Proper Four-Colorings on Cubic Graphs

Graph coloring is arguably the most exhaustively studied problem in the area of approximate counting. It is conjectured that there is a fully polynomial-time (randomized) approximation scheme (FPTAS/FPRAS) for counting the number of proper colorings as long as $q \geq Δ+ 1$, where $q$ is the number of colors and $Δ$ is the maximum degree of the graph. The bound of $q = Δ+ 1$ is the uniqueness threshold for Gibbs measure on $Δ$-regular infinite trees. However, the conjecture remained open even for any fixed $Δ\geq 3$ (The cases of $Δ=1, 2$ are trivial). In this paper, we design an FPTAS for counting the number of proper $4$-colorings on graphs with maximum degree $3$ and thus confirm the conjecture in the case of $Δ=3$. This is the first time to achieve this optimal bound of $q = Δ+ 1$. Previously, the best FPRAS requires $q > \frac{11}{6} Δ$ and the best deterministic FPTAS requires $q > 2.581Δ+ 1$ for general graphs. In the case of $Δ=3$, the best previous result is an FPRAS for counting proper 5-colorings. We note that there is a barrier to go beyond $q = Δ+ 2$ for single-site Glauber dynamics based FPRAS and we overcome this by correlation decay approach. Moreover, we develop a number of new techniques for the correlation decay approach which can find applications in other approximate counting problems.

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Canonical Paths for MCMC: from Art to Science

Markov Chain Monte Carlo (MCMC) method is a widely used algorithm design scheme with many applications. To make efficient use of this method, the key step is to prove that the Markov chain is rapid mixing. Canonical paths is one of the two main tools to prove rapid mixing. However, there are much fewer success examples comparing to coupling, the other main tool. The main reason is that there is no systematic approach or general recipe to design canonical paths. Building up on a previous exploration by McQuillan, we develop a general theory to design canonical paths for MCMC: We reduce the task of designing canonical paths to solving a set of linear equations, which can be automatically done even by a machine. Making use of this general approach, we obtain fully polynomial-time randomized approximation schemes (FPRAS) for counting the number of $b$-matching with $b\leq 7$ and $b$-edge-cover with $b\leq 2$. They are natural generalizations of matchings and edge covers for graphs. No polynomial time approximation was previously known for these problems.

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FPTAS for Hardcore and Ising Models on Hypergraphs

Hardcore and Ising models are two most important families of two state spin systems in statistic physics. Partition function of spin systems is the center concept in statistic physics which connects microscopic particles and their interactions with their macroscopic and statistical properties of materials such as energy, entropy, ferromagnetism, etc. If each local interaction of the system involves only two particles, the system can be described by a graph. In this case, fully polynomial-time approximation scheme (FPTAS) for computing the partition function of both hardcore and anti-ferromagnetic Ising model was designed up to the uniqueness condition of the system. These result are the best possible since approximately computing the partition function beyond this threshold is NP-hard. In this paper, we generalize these results to general physics systems, where each local interaction may involves multiple particles. Such systems are described by hypergraphs. For hardcore model, we also provide FPTAS up to the uniqueness condition, and for anti-ferromagnetic Ising model, we obtain FPTAS where a slightly stronger condition holds.

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FPTAS for #BIS with Degree Bounds on One Side

Counting the number of independent sets for a bipartite graph (#BIS) plays a crucial role in the study of approximate counting. It has been conjectured that there is no fully polynomial-time (randomized) approximation scheme (FPTAS/FPRAS) for #BIS, and it was proved that the problem for instances with a maximum degree of $6$ is already as hard as the general problem. In this paper, we obtain a surprising tractability result for a family of #BIS instances. We design a very simple deterministic fully polynomial-time approximation scheme (FPTAS) for #BIS when the maximum degree for one side is no larger than $5$. There is no restriction for the degrees on the other side, which do not even have to be bounded by a constant. Previously, FPTAS was only known for instances with a maximum degree of $5$ for both sides.

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Improved Efficiency Guarantees in Auctions with Budgets

We study the efficiency guarantees in the simple auction environment where the auctioneer has one unit of divisible good to be distributed among a number of budget constrained agents. With budget constraints, the social welfare cannot be approximated by a better factor than the number of agents by any truthful mechanism. Thus, we follow a recent work by Dobzinski and Leme (ICALP 2014) to approximate the liquid welfare, which is the welfare of the agents each capped by her/his own budget. We design a new truthful auction with an approximation ratio of $\frac{\sqrt{5}+1}{2} \approx 1.618$, improving the best previous ratio of $2$ when the budgets for agents are public knowledge and their valuation is linear (additive). In private budget setting, we propose the first constant approximation auction with approximation ratio of $34$. Moreover, this auction works for any valuation function. Previously, only $O(\log n)$ approximation was known for linear and decreasing marginal (concave) valuations, and $O(\log^2 n)$ approximation was known for sub-additive valuations.

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Competitive analysis via benchmark decomposition

We propose a uniform approach for the design and analysis of prior-free competitive auctions and online auctions. Our philosophy is to view the benchmark function as a variable parameter of the model and study a broad class of functions instead of a individual target benchmark. We consider a multitude of well-studied auction settings, and improve upon a few previous results. (1) Multi-unit auctions. Given a $β$-competitive unlimited supply auction, the best previously known multi-unit auction is $2β$-competitive. We design a $(1+β)$-competitive auction reducing the ratio from $4.84$ to $3.24$. These results carry over to matroid and position auctions. (2) General downward-closed environments. We design a $6.5$-competitive auction improving upon the ratio of $7.5$. Our auction is noticeably simpler than the previous best one. (3) Unlimited supply online auctions. Our analysis yields an auction with a competitive ratio of $4.12$, which significantly narrows the margin of $[4,4.84]$ previously known for this problem. A particularly important tool in our analysis is a simple decomposition lemma, which allows us to bound the competitive ratio against a sum of benchmark functions. We use this lemma in a "divide and conquer" fashion by dividing the target benchmark into the sum of simpler functions.

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The complexity of approximating conservative counting CSPs

We study the complexity of approximately solving the weighted counting constraint satisfaction problem #CSP(F). In the conservative case, where F contains all unary functions, there is a classification known for the case in which the domain of functions in F is Boolean. In this paper, we give a classification for the more general problem where functions in F have an arbitrary finite domain. We define the notions of weak log-modularity and weak log-supermodularity. We show that if F is weakly log-modular, then #CSP(F)is in FP. Otherwise, it is at least as difficult to approximate as #BIS, the problem of counting independent sets in bipartite graphs. #BIS is complete with respect to approximation-preserving reductions for a logically-defined complexity class #RHPi1, and is believed to be intractable. We further sub-divide the #BIS-hard case. If F is weakly log-supermodular, then we show that #CSP(F) is as easy as a (Boolean) log-supermodular weighted #CSP. Otherwise, we show that it is NP-hard to approximate. Finally, we give a full trichotomy for the arity-2 case, where #CSP(F) is in FP, or is #BIS-equivalent, or is equivalent in difficulty to #SAT, the problem of approximately counting the satisfying assignments of a Boolean formula in conjunctive normal form. We also discuss the algorithmic aspects of our classification.

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FPTAS for Counting Monotone CNF

A monotone CNF formula is a Boolean formula in conjunctive normal form where each variable appears positively. We design a deterministic fully polynomial-time approximation scheme (FPTAS) for counting the number of satisfying assignments for a given monotone CNF formula when each variable appears in at most $5$ clauses. Equivalently, this is also an FPTAS for counting set covers where each set contains at most $5$ elements. If we allow variables to appear in a maximum of $6$ clauses (or sets to contain $6$ elements), it is NP-hard to approximate it. Thus, this gives a complete understanding of the approximability of counting for monotone CNF formulas. It is also an important step towards a complete characterization of the approximability for all bounded degree Boolean #CSP problems. In addition, we study the hypergraph matching problem, which arises naturally towards a complete classification of bounded degree Boolean #CSP problems, and show an FPTAS for counting 3D matchings of hypergraphs with maximum degree $4$. Our main technique is correlation decay, a powerful tool to design deterministic FPTAS for counting problems defined by local constraints among a number of variables. All previous uses of this design technique fall into two categories: each constraint involves at most two variables, such as independent set, coloring, and spin systems in general; or each variable appears in at most two constraints, such as matching, edge cover, and holant problem in general. The CNF problems studied here have more complicated structures than these problems and require new design and proof techniques. As it turns out, the technique we developed for the CNF problem also works for the hypergraph matching problem. We believe that it may also find applications in other CSP or more general counting problems.

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The Complexity of Ferromagnetic Two-spin Systems with External Fields

We study the approximability of computing the partition function for ferromagnetic two-state spin systems. The remarkable algorithm by Jerrum and Sinclair showed that there is a fully polynomial-time randomized approximation scheme (FPRAS) for the special ferromagnetic Ising model with any given uniform external field. Later, Goldberg and Jerrum proved that it is #BIS-hard for Ising model if we allow inconsistent external fields on different nodes. In contrast to these two results, we prove that for any ferromagnetic two-state spin systems except the Ising model, there exists a threshold for external fields beyond which the problem is #BIS-hard, even if the external field is uniform.

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FPTAS for Weighted Fibonacci Gates and Its Applications

Fibonacci gate problems have severed as computation primitives to solve other problems by holographic algorithm and play an important role in the dichotomy of exact counting for Holant and CSP frameworks. We generalize them to weighted cases and allow each vertex function to have different parameters, which is a much boarder family and #P-hard for exactly counting. We design a fully polynomial-time approximation scheme (FPTAS) for this generalization by correlation decay technique. This is the first deterministic FPTAS for approximate counting in the general Holant framework without a degree bound. We also formally introduce holographic reduction in the study of approximate counting and these weighted Fibonacci gate problems serve as computation primitives for approximate counting. Under holographic reduction, we obtain FPTAS for other Holant problems and spin problems. One important application is developing an FPTAS for a large range of ferromagnetic two-state spin systems. This is the first deterministic FPTAS in the ferromagnetic range for two-state spin systems without a degree bound. Besides these algorithms, we also develop several new tools and techniques to establish the correlation decay property, which are applicable in other problems.

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Optimal Competitive Auctions

We study the design of truthful auctions for selling identical items in unlimited supply (e.g., digital goods) to n unit demand buyers. This classic problem stands out from profit-maximizing auction design literature as it requires no probabilistic assumptions on buyers' valuations and employs the framework of competitive analysis. Our objective is to optimize the worst-case performance of an auction, measured by the ratio between a given benchmark and revenue generated by the auction. We establish a sufficient and necessary condition that characterizes competitive ratios for all monotone benchmarks. The characterization identifies the worst-case distribution of instances and reveals intrinsic relations between competitive ratios and benchmarks in the competitive analysis. With the characterization at hand, we show optimal competitive auctions for two natural benchmarks. The most well-studied benchmark $\mathcal{F}^{(2)}(\cdot)$ measures the envy-free optimal revenue where at least two buyers win. Goldberg et al. [13] showed a sequence of lower bounds on the competitive ratio for each number of buyers n. They conjectured that all these bounds are tight. We show that optimal competitive auctions match these bounds. Thus, we confirm the conjecture and settle a central open problem in the design of digital goods auctions. As one more application we examine another economically meaningful benchmark, which measures the optimal revenue across all limited-supply Vickrey auctions. We identify the optimal competitive ratios to be $(\frac{n}{n-1})^{n-1}-1$ for each number of buyers n, that is $e-1$ as $n$ approaches infinity.

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A Simple FPTAS for Counting Edge Covers

An edge cover of a graph is a set of edges such that every vertex has at least an adjacent edge in it. Previously, approximation algorithm for counting edge covers is only known for 3 regular graphs and it is randomized. We design a very simple deterministic fully polynomial-time approximation scheme (FPTAS) for counting the number of edge covers for any graph. Our main technique is correlation decay, which is a powerful tool to design FPTAS for counting problems. In order to get FPTAS for general graphs without degree bound, we make use of a stronger notion called computationally efficient correlation decay, which is introduced in [Li, Lu, Yin SODA 2012].

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Dichotomy for Holant* Problems with a Function on Domain Size 3

Holant problems are a general framework to study the algorithmic complexity of counting problems. Both counting constraint satisfaction problems and graph homomorphisms are special cases. All previous results of Holant problems are over the Boolean domain. In this paper, we give the first dichotomy theorem for Holant problems for domain size $>2$. We discover unexpected tractable families of counting problems, by giving new polynomial time algorithms. This paper also initiates holographic reductions in domains of size $>2$. This is our main algorithmic technique, and is used for both tractable families and hardness reductions. The dichotomy theorem is the following: For any complex-valued symmetric function ${\bf F}$ with arity 3 on domain size 3, we give an explicit criterion on ${\bf F}$, such that if ${\bf F}$ satisfies the criterion then the problem ${\rm Holant}^*({\bf F})$ is computable in polynomial time, otherwise ${\rm Holant}^*({\bf F})$ is #P-hard.

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Inapproximability After Uniqueness Phase Transition in Two-Spin Systems

A two-state spin system is specified by a 2 x 2 matrix A = {A_{0,0} A_{0,1}, A_{1,0} A_{1,1}} = {β1, 1 γ} where β, γ\ge 0. Given an input graph G=(V,E), the partition function Z_A(G) of a system is defined as Z_A(G) = \sum_{σ: V -> {0,1}} \prod_{(u,v) \in E} A_{σ(u), σ(v)} We prove inapproximability results for the partition function in the region specified by the non-uniqueness condition from phase transition for the Gibbs measure. More specifically, assuming NP \ne RP, for any fixed β, γin the unit square, there is no randomized polynomial-time algorithm that approximates Z_A(G) for d-regular graphs G with relative error ε= 10^{-4}, if d = Ω(Δ(β,γ)), where Δ(β,γ) > 1/(1-βγ) is the uniqueness threshold. Up to a constant factor, this hardness result confirms the conjecture that the uniqueness phase transition coincides with the transition from computational tractability to intractability for Z_A(G). We also show a matching inapproximability result for a region of parameters β, γoutside the unit square, and all our results generalize to partition functions with an external field.

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Budget Feasible Mechanism Design via Random Sampling

Budget feasible mechanism considers algorithmic mechanism design questions where there is a budget constraint on the total payment of the mechanism. An important question in the field is that under which valuation domains there exist budget feasible mechanisms that admit `small' approximations (compared to a socially optimal solution). Singer \cite{PS10} showed that additive and submodular functions admit a constant approximation mechanism. Recently, Dobzinski, Papadimitriou, and Singer \cite{DPS11} gave an $O(\log^2n)$ approximation mechanism for subadditive functions and remarked that: "A fundamental question is whether, regardless of computational constraints, a constant-factor budget feasible mechanism exists for subadditive function." In this paper, we give the first attempt to this question. We give a polynomial time $O(\frac{\log n}{\log\log n})$ sub-logarithmic approximation ratio mechanism for subadditive functions, improving the best known ratio $O(\log^2 n)$. Further, we connect budget feasible mechanism design to the concept of approximate core in cooperative game theory, and show that there is a mechanism for subadditive functions whose approximation is, via a characterization of the integrality gap of a linear program, linear to the largest value to which an approximate core exists. Our result implies in particular that the class of XOS functions, which is a superclass of submodular functions, admits a constant approximation mechanism. We believe that our work could be a solid step towards solving the above fundamental problem eventually, and possibly, with an affirmative answer.

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Budget Feasible Mechanism Design: From Prior-Free to Bayesian

Budget feasible mechanism design studies procurement combinatorial auctions where the sellers have private costs to produce items, and the buyer(auctioneer) aims to maximize a social valuation function on subsets of items, under the budget constraint on the total payment. One of the most important questions in the field is "which valuation domains admit truthful budget feasible mechanisms with `small' approximations (compared to the social optimum)?" Singer showed that additive and submodular functions have such constant approximations. Recently, Dobzinski, Papadimitriou, and Singer gave an O(log^2 n)-approximation mechanism for subadditive functions; they also remarked that: "A fundamental question is whether, regardless of computational constraints, a constant-factor budget feasible mechanism exists for subadditive functions." We address this question from two viewpoints: prior-free worst case analysis and Bayesian analysis. For the prior-free framework, we use an LP that describes the fractional cover of the valuation function; it is also connected to the concept of approximate core in cooperative game theory. We provide an O(I)-approximation mechanism for subadditive functions, via the worst case integrality gap I of LP. This implies an O(log n)-approximation for subadditive valuations, O(1)-approximation for XOS valuations, and for valuations with a constant I. XOS valuations are an important class of functions that lie between submodular and subadditive classes. We give another polynomial time O(log n/loglog n) sub-logarithmic approximation mechanism for subadditive valuations. For the Bayesian framework, we provide a constant approximation mechanism for all subadditive functions, using the above prior-free mechanism for XOS valuations as a subroutine. Our mechanism allows correlations in the distribution of private information and is universally truthful.

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