arXiv subjects

Rahul Jain

Publications and source records attributed to Rahul Jain.

At least 145 records · Page 8Linked to original sources

arXiv2017

Quantum message compression with applications

We present a new scheme for the compression of one-way quantum messages, in the setting of coherent entanglement assisted quantum communication. For this, we present a new technical tool that we call the convex split lemma, which is inspired by the classical compression schemes that use rejection sampling procedure. As a consequence, we show new bounds on the quantum communication cost of single-shot entanglement-assisted one-way quantum state redistribution task and for the sub-tasks quantum state splitting and quantum state merging. Our upper and lower bounds are tight up to a constant and hence stronger than previously known best bounds for above tasks. Our protocols use explicit quantum operations on the sides of Alice and Bob, which are different from the decoupling by random unitaries approach used in previous works. As another application, we present a port-based teleportation scheme which works when the set of input states is restricted to a known ensemble, hence potentially saving the number of required ports. Furthermore, in case of no prior knowledge about the set of input states, our average success fidelity matches the known average success fidelity, providing a new port-based teleportation scheme with similar performance as appears in literature.

quant-ph↗

arXiv2016

Matching Multiplications in Bit-Vector Formulas

Bit-vector formulas arising from hardware verification problems often contain word-level arithmetic operations. Empirical evidence shows that state-of-the-art SMT solvers are not very efficient at reasoning about bit-vector formulas with multiplication. This is particularly true when multiplication operators are decomposed and represented in alternative ways in the formula.We present a pre-processing heuristic that identifies certain types of decomposed multipliers, and adds special assertions to the input formula encoding the equivalence of sub-terms to word-level multiplication. The pre-processed formulas are then solved using an SMT solver. Our experiments with three SMT solvers show that our heuristic allows several formulas to be solved quickly, while the same formulas time out without the pre-processing step.

cs.LO↗

arXiv2016

On Regret-Optimal Learning in Decentralized Multi-player Multi-armed Bandits

We consider the problem of learning in single-player and multiplayer multiarmed bandit models. Bandit problems are classes of online learning problems that capture exploration versus exploitation tradeoffs. In a multiarmed bandit model, players can pick among many arms, and each play of an arm generates an i.i.d. reward from an unknown distribution. The objective is to design a policy that maximizes the expected reward over a time horizon for a single player setting and the sum of expected rewards for the multiplayer setting. In the multiplayer setting, arms may give different rewards to different players. There is no separate channel for coordination among the players. Any attempt at communication is costly and adds to regret. We propose two decentralizable policies, $\tt E^3$ ($\tt E$-$\tt cubed$) and $\tt E^3$-$\tt TS$, that can be used in both single player and multiplayer settings. These policies are shown to yield expected regret that grows at most as O($\log^{1+ε} T$). It is well known that $\log T$ is the lower bound on the rate of growth of regret even in a centralized case. The proposed algorithms improve on prior work where regret grew at O($\log^2 T$). More fundamentally, these policies address the question of additional cost incurred in decentralized online learning, suggesting that there is at most an $ε$-factor cost in terms of order of regret. This solves a problem of relevance in many domains and had been open for a while.

stat.ML↗

arXiv2016

Optimal Decentralized Control with Asymmetric One-Step Delayed Information Sharing

We consider optimal control of decentralized LQG problems for plants controlled by two players having asymmetric information sharing patterns between them. In one scenario, players are assumed to have a bidirectional error-free, unlimited rate communication channel with no delay in one direction and a unit delay in the other. In another scenario, the communication channel is assumed to be unidirectional with a unit delay. Delayed information sharing patterns in general do not admit linear optimal control laws and are thus difficult to control optimally. However, in these scenarios, we show that the problem has a partially nested information structure, and thus linear optimal control laws exist. Summary statistics to characterize these laws are developed and deterministic convex optimization problems are formulated whose solutions yield the optimal control laws. The state feedback case is solved for both scenarios and extended to output and partial output feedback in case of bidirectional and unidirectional channels respectively.

math.OC↗

arXiv2016

Separating quantum communication and approximate rank

One of the best lower bound methods for the quantum communication complexity of a function H (with or without shared entanglement) is the logarithm of the approximate rank of the communication matrix of H. This measure is essentially equivalent to the approximate gamma_2 norm and generalized discrepancy, and subsumes several other lower bounds. All known lower bounds on quantum communication complexity in the general unbounded-round model can be shown via the logarithm of approximate rank, and it was an open problem to give any separation at all between quantum communication complexity and the logarithm of the approximate rank. In this work we provide the first such separation: We exhibit a total function H with quantum communication complexity almost quadratically larger than the logarithm of its approximate rank. We construct H using the communication lookup function framework of Anshu et al. (FOCS 2016) based on the cheat sheet framework of Aaronson et al. (STOC 2016). From a starting function F, this framework defines a new function H=F_G. Our main technical result is a lower bound on the quantum communication complexity of F_G in terms of the discrepancy of F, which we do via quantum information theoretic arguments. We show the upper bound on the approximate rank of F_G by relating it to the Boolean circuit size of the starting function F.

quant-ph↗

arXiv2016

Separations in communication complexity using cheat sheets and information complexity

While exponential separations are known between quantum and randomized communication complexity for partial functions (Raz, STOC 1999), the best known separation between these measures for a total function is quadratic, witnessed by the disjointness function. We give the first super-quadratic separation between quantum and randomized communication complexity for a total function, giving an example exhibiting a power 2.5 gap. We further present a 1.5 power separation between exact quantum and randomized communication complexity, improving on the previous ~1.15 separation by Ambainis (STOC 2013). Finally, we present a nearly optimal quadratic separation between randomized communication complexity and the logarithm of the partition number, improving upon the previous best power 1.5 separation due to Göös, Jayram, Pitassi, and Watson. Our results are the communication analogues of separations in query complexity proved using the recent cheat sheet framework of Aaronson, Ben-David, and Kothari (STOC 2016). Our main technical results are randomized communication and information complexity lower bounds for a family of functions, called lookup functions, that generalize and port the cheat sheet framework to communication complexity.

quant-ph↗

arXiv2016

Approachability in Stackelberg Stochastic Games with Vector Costs

The notion of approachability was introduced by Blackwell [1] in the context of vector-valued repeated games. The famous Blackwell's approachability theorem prescribes a strategy for approachability, i.e., for `steering' the average cost of a given agent towards a given target set, irrespective of the strategies of the other agents. In this paper, motivated by the multi-objective optimization/decision making problems in dynamically changing environments, we address the approachability problem in Stackelberg stochastic games with vector valued cost functions. We make two main contributions. Firstly, we give a simple and computationally tractable strategy for approachability for Stackelberg stochastic games along the lines of Blackwell's. Secondly, we give a reinforcement learning algorithm for learning the approachable strategy when the transition kernel is unknown. We also recover as a by-product Blackwell's necessary and sufficient condition for approachability for convex sets in this set up and thus a complete characterization. We also give sufficient conditions for non-convex sets.

cs.LG↗

arXiv2016

Asynchronous Optimization Over Heterogeneous Networks via Consensus ADMM

This paper considers the distributed optimization of a sum of locally observable, non-convex functions. The optimization is performed over a multi-agent networked system, and each local function depends only on a subset of the variables. An asynchronous and distributed alternating directions method of multipliers (ADMM) method that allows the nodes to defer or skip the computation and transmission of updates is proposed in the paper. The proposed algorithm utilizes different approximations in the update step, resulting in proximal and majorized ADMM variants. Both variants are shown to converge to a local minimum, under certain regularity conditions. The proposed asynchronous algorithms are also applied to the problem of cooperative localization in wireless ad hoc networks, where it is shown to outperform the other state-of-the-art localization algorithms.

math.OC↗

arXiv2016

Partition bound is quadratically tight for product distributions

Let $f : \{0,1\}^n \times \{0,1\}^n \rightarrow \{0,1\}$ be a 2-party function. For every product distribution $μ$ on $\{0,1\}^n \times \{0,1\}^n$, we show that $$\mathsf{CC}^μ_{0.49}(f) = O\left(\left(\log \mathsf{prt}_{1/8}(f) \cdot \log \log \mathsf{prt}_{1/8}(f)\right)^2\right),$$ where $\mathsf{CC}^μ_\varepsilon(f)$ is the distributional communication complexity of $f$ with error at most $\varepsilon$ under the distribution $μ$ and $\mathsf{prt}_{1/8}(f)$ is the {\em partition bound} of $f$, as defined by Jain and Klauck [{\em Proc. 25th CCC}, 2010]. We also prove a similar bound in terms of $\mathsf{IC}_{1/8}(f)$, the {\em information complexity} of $f$, namely, $$\mathsf{CC}^μ_{0.49}(f) = O\left(\left(\mathsf{IC}_{1/8}(f) \cdot \log \mathsf{IC}_{1/8}(f)\right)^2\right).$$ The latter bound was recently and independently established by Kol [{\em Proc. 48th STOC}, 2016] using a different technique. We show a similar result for query complexity under product distributions. Let $g : \{0,1\}^n \rightarrow \{0,1\}$ be a function. For every bit-wise product distribution $μ$ on $\{0,1\}^n$, we show that $$\mathsf{QC}^μ_{0.49}(g) = O\left(\left( \log \mathsf{qprt}_{1/8}(g) \cdot \log \log\mathsf{qprt}_{1/8}(g) \right)^2 \right),$$ where $\mathsf{QC}^μ_{\varepsilon}(g)$ is the distributional query complexity of $f$ with error at most $\varepsilon$ under the distribution $μ$ and $\mathsf{qprt}_{1/8}(g))$ is the {\em query partition bound} of the function $g$. Partition bounds were introduced (in both communication complexity and query complexity models) to provide LP-based lower bounds for randomized communication complexity and randomized query complexity. Our results demonstrate that these lower bounds are polynomially tight for {\em product} distributions.

cs.CC↗

arXiv2016

Extension Complexity of Independent Set Polytopes

We exhibit an $n$-node graph whose independent set polytope requires extended formulations of size exponential in $Ω(n/\log n)$. Previously, no explicit examples of $n$-dimensional $0/1$-polytopes were known with extension complexity larger than exponential in $Θ(\sqrt{n})$. Our construction is inspired by a relatively little-known connection between extended formulations and (monotone) circuit depth.

cs.CC↗

arXiv2015

Communication tasks with infinite quantum-classical separation

Quantum resources can be more powerful than classical resources - a quantum computer can solve certain problems exponentially faster than a classical computer, and computing a function of two people's inputs can be done with exponentially less communication with quantum messages than with classical ones. Here we consider a task between two players, Alice and Bob where quantum resources are infinitely more powerful than classical ones. Alice is given a string of length n, and Bob's task is to exclude certain combinations of bits that Alice might have. If Alice must send classical messages, then she must reveal nearly n bits of information to Bob, but if she is allowed to send quantum bits, the amount of information she must reveal goes to zero with increasing n. Next, we consider a version of the task where the parties can only send classical messages but may have access to entanglement. When assisted by entanglement, Alice only needs to send a constant number of bits, while without entanglement, the number of bits Alice must send grows linearly with n. The task is related to the PBR theorem which arises in the context of the foundations of quantum theory.

quant-ph↗

arXiv2015

New one shot quantum protocols with application to communication complexity

In this paper we present the following quantum compression protocol: P : Let $ρ,σ$ be quantum states such that $S(ρ|| σ) = \text{Tr} (ρ\log ρ- ρ\log σ)$, the relative entropy between $ρ$ and $σ$, is finite. Alice gets to know the eigen-decomposition of $ρ$. Bob gets to know the eigen-decomposition of $σ$. Both Alice and Bob know $S(ρ|| σ)$ and an error parameter $ε$. Alice and Bob use shared entanglement and after communication of $\mathcal{O}((S(ρ|| σ)+1)/ε^4)$ bits from Alice to Bob, Bob ends up with a quantum state $\tildeρ$ such that $F(ρ, \tildeρ) \geq 1 - 5ε$, where $F(\cdot)$ represents fidelity. This result can be considered as a non-commutative generalization of a result due to Braverman and Rao [2011] where they considered the special case when $ρ$ and $σ$ are classical probability distributions (or commute with each other) and use shared randomness instead of shared entanglement. We use P to obtain an alternate proof of a direct-sum result for entanglement assisted quantum one-way communication complexity for all relations, which was first shown by Jain, Radhakrishnan and Sen [2005,2008]. We also present a variant of protocol P in which Bob has some side information about the state with Alice. We show that in such a case, the amount of communication can be further reduced, based on the side information that Bob has. Our second result provides a quantum analogue of the widely used classical correlated-sampling protocol. For example, Holenstein [2007] used the classical correlated-sampling protocol in his proof of a parallel-repetition theorem for two-player one-round games.

quant-ph↗

arXiv2014

On Transitory Queueing

We introduce a framework and develop a theory of transitory queueing models. These are models that are not only non-stationary and time-varying but also have other features such as the queueing system operates over finite time, or only a finite population arrives. Such models are relevant in many real-world settings, from queues at post-offces, DMV, concert halls and stadia to out-patient departments at hospitals. We develop fluid and diffusion limits for a large class of transitory queueing models. We then introduce three specific models that fit within this framework, namely, the Delta(i)/GI/1 model, the conditioned G/GI/1 model, and an arrival model of scheduled traffic with epoch uncertainty. We show that asymptotically these models are distributionally equivalent, i.e., they have the same fluid and diffusion limits. We note that our framework provides the first ever way of analyzing the standard G/GI/1 model when we condition on the number of arrivals. In obtaining these results, we provide generalizations and extensions of the Glivenko-Cantelli and Donskers Theorem for empirical processes with triangular arrays. Our analysis uses the population acceleration technique that we introduce and develop. This may be useful in analysis of other non-stationary and non-ergodic queuing models.

math.PR↗

arXiv2014

A queueing model with independent arrivals, and its fluid and diffusion limits

We introduce the Δ(i)/GI/1 queue, a new queueing model. In this model, customers from a given population independently sample a time to arrive from some given distribution F. Thus, the arrival times are an ordered statistics, and the inter-arrival times are differences of consecutive ordered statistics. They are served by a single server which provides service according to a general distribution G, with independent service times. The exact model is analytically intractable. Thus, we develop fluid and diffusion limits for the various stochastic processes, and performance metrics. The fluid limit of the queue length is observed to be a reflected process, while the diffusion limit is observed to be a function of a Brownian motion and a Brownian bridge process, and is given by a 'netput' process and a directional derivative of the Skorokhod reflected fluid netput in the direction of a diffusion refinement of the netput process. We also observe what may be interpreted as a transient Little's law. Sample path analysis reveals various operating regimes where the diffusion limit switches between a free diffusion, a reflected diffusion process and the zero process, with possible discontinuities during regime switches. The weak convergence is established in the M1 topology, and it is also shown that this is not possible in the J1 topology.

math.PR↗

arXiv2014

Unidirectional Input/Output Streaming Complexity of Reversal and Sorting

We consider unidirectional data streams with restricted access, such as read-only and write-only streams. For read-write streams, we also introduce a new complexity measure called expansion, the ratio between the space used on the stream and the input size. We give tight bounds for the complexity of reversing a stream of length $n$ in several of the possible models. In the read-only and write-only model, we show that $p$-pass algorithms need memory space $Θ(n/p)$. But if either the output stream or the input stream is read-write, then the complexity falls to $Θ(n/p^2)$. It becomes $polylog(n)$ if $p = O(log n)$ and both streams are read-write. We also study the complexity of sorting a stream and give two algorithms with small expansion. Our main sorting algorithm is randomized and has $O(1)$ expansion, $O(log n)$ passes and $O(log n)$ memory.

cs.DS↗

arXiv2014

Multipartite Quantum Correlation and Communication Complexities

The concepts of quantum correlation complexity and quantum communication complexity were recently proposed to quantify the minimum amount of resources needed in generating bipartite classical or quantum states in the single-shot setting. The former is the minimum size of the initially shared state $σ$ on which local operations by the two parties (without communication) can generate the target state $ρ$, and the latter is the minimum amount of communication needed when initially sharing nothing. In this paper, we generalize these two concepts to multipartite cases, for both exact and approximate state generation. Our results are summarized as follows. (1) For multipartite pure states, the correlation complexity can be completely characterized by local ranks of sybsystems. (2) We extend the notion of PSD-rank of matrices to that of tensors, and use it to bound the quantum correlation complexity for generating multipartite classical distributions. (3) For generating multipartite mixed quantum states, communication complexity is not always equal to correlation complexity (as opposed to bipartite case). But they differ by at most a factor of 2. Generating a multipartite mixed quantum state has the same communication complexity as generating its optimal purification. But for correlation complexity of these two tasks can be different (though still related by less than a factor of 2). (4) To generate a bipartite classical distribution $P(x,y)$ approximately, the quantum communication complexity is completely characterized by the approximate PSD-rank of $P$. The quantum correlation complexity of approximately generating multipartite pure states is bounded by approximate local ranks.

quant-ph↗

arXiv2014

A strong direct product theorem for the tribes function via the smooth-rectangle bound

The main result of this paper is an optimal strong direct product result for the two-party public-coin randomized communication complexity of the Tribes function. This is proved by providing an alternate proof of the optimal lower bound of Ω(n) for the randomised communication complexity of the Tribes function using the so-called smooth-rectangle bound, introduced by Jain and Klauck [JK10]. The optimal Ω(n) lower bound for Tribes was originally proved by Jayram, Kumar and Sivakumar [JKS03], using a more powerful lower bound technique, namely the information complexity bound. The information complexity bound is known to be at least as strong a lower bound method as the smooth-rectangle bound [KLL+12]. On the other hand, we are not aware of any function or relation for which the smooth-rectangle bound is (asymptotically) smaller than its public-coin randomized communication complexity. The optimal direct product for Tribes is obtained by combining our smooth-rectangle bound for tribes with the strong direct product result of Jain and Yao [JY12] in terms of smooth-rectangle bound.

cs.CC↗

arXiv2014

The space complexity of recognizing well-parenthesized expressions in the streaming model: the Index function revisited

We show an Omega(sqrt{n}/T) lower bound for the space required by any unidirectional constant-error randomized T-pass streaming algorithm that recognizes whether an expression over two types of parenthesis is well-parenthesized. This proves a conjecture due to Magniez, Mathieu, and Nayak (2009) and rigorously establishes that bidirectional streams are exponentially more efficient in space usage as compared with unidirectional ones. We obtain the lower bound by establishing the minimum amount of information that is necessarily revealed by the players about their respective inputs in a two-party communication protocol for a variant of the Index function, namely Augmented Index. The information cost trade-off is obtained by a novel application of the conceptually simple and familiar ideas such as average encoding and the cut-and-paste property of randomized protocols. Motivated by recent examples of exponential savings in space by streaming quantum algorithms, we also study quantum protocols for Augmented Index. Defining an appropriate notion of information cost for quantum protocols involves a delicate balancing act between its applicability and the ease with which we can analyze it. We define a notion of quantum information cost which reflects some of the non-intuitive properties of quantum information and give a trade-off for this notion. While this trade-off demonstrates the strength of our proof techniques, it does not lead to a space lower bound for checking parentheses. We leave such an implication for quantum streaming algorithms as an intriguing open question.

cs.CC↗